Overview

Dataset statistics

Number of variables54
Number of observations671
Missing cells5011
Missing cells (%)13.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory272.7 KiB
Average record size in memory416.2 B

Variable types

Categorical40
Numeric3
DateTime6
Unsupported5

Alerts

context has constant value ""Constant
type has constant value ""Constant
actor_type has constant value ""Constant
object_type has constant value ""Constant
edapp_type has constant value ""Constant
referrer_type has constant value ""Constant
session_type has constant value ""Constant
extensions_caliperversion has constant value ""Constant
extensions_caliperappversion has constant value ""Constant
id has a high cardinality: 667 distinct valuesHigh cardinality
actor_id has a high cardinality: 285 distinct valuesHigh cardinality
actor_extensions_userid has a high cardinality: 285 distinct valuesHigh cardinality
actor_extensions_userteacherid has a high cardinality: 158 distinct valuesHigh cardinality
actor_extensions_userparentid has a high cardinality: 123 distinct valuesHigh cardinality
eventtime_kst has a high cardinality: 667 distinct valuesHigh cardinality
object_id has a high cardinality: 234 distinct valuesHigh cardinality
object_name has a high cardinality: 232 distinct valuesHigh cardinality
object_datetostarton_kst has a high cardinality: 277 distinct valuesHigh cardinality
object_datetosubmit_kst has a high cardinality: 201 distinct valuesHigh cardinality
referrer_id has a high cardinality: 234 distinct valuesHigh cardinality
session_id has a high cardinality: 285 distinct valuesHigh cardinality
session_startedattime_kst has a high cardinality: 286 distinct valuesHigh cardinality
session_extensions_userid has a high cardinality: 285 distinct valuesHigh cardinality
in_datetime_kst has a high cardinality: 671 distinct valuesHigh cardinality
actor_extensions_userpost is highly overall correlated with actor_extensions_usertype and 14 other fieldsHigh correlation
referrer_extensions_assignmentgrade is highly overall correlated with actor_extensions_userlevel and 3 other fieldsHigh correlation
referrer_extensions_assignmentlchapter is highly overall correlated with referrer_extensions_assignmenttypeHigh correlation
actor_extensions_usertype is highly overall correlated with actor_extensions_userpost and 2 other fieldsHigh correlation
actor_extensions_usertypename is highly overall correlated with actor_extensions_userpost and 2 other fieldsHigh correlation
actor_extensions_usertypedescription is highly overall correlated with actor_extensions_userpost and 2 other fieldsHigh correlation
actor_extensions_userlevel is highly overall correlated with actor_extensions_userpost and 5 other fieldsHigh correlation
actor_extensions_usergrade is highly overall correlated with actor_extensions_userpost and 2 other fieldsHigh correlation
edapp_id is highly overall correlated with actor_extensions_userpost and 6 other fieldsHigh correlation
edapp_name is highly overall correlated with actor_extensions_userpost and 6 other fieldsHigh correlation
edapp_description is highly overall correlated with actor_extensions_userpost and 5 other fieldsHigh correlation
edapp_version is highly overall correlated with actor_extensions_userpost and 7 other fieldsHigh correlation
referrer_extensions_assignmenttype is highly overall correlated with actor_extensions_userpost and 10 other fieldsHigh correlation
referrer_extensions_assignmentsubjectid is highly overall correlated with actor_extensions_userpost and 7 other fieldsHigh correlation
referrer_extensions_assignmentsemester is highly overall correlated with actor_extensions_userpost and 1 other fieldsHigh correlation
referrer_extensions_assignmentmchapter is highly overall correlated with actor_extensions_userpost and 3 other fieldsHigh correlation
referrer_extensions_assignmentprogday_kst is highly overall correlated with actor_extensions_userpost and 6 other fieldsHigh correlation
extensions_timezone is highly overall correlated with actor_extensions_userpost and 1 other fieldsHigh correlation
actor_extensions_usertype is highly imbalanced (60.1%)Imbalance
actor_extensions_usertypename is highly imbalanced (60.1%)Imbalance
actor_extensions_usertypedescription is highly imbalanced (60.1%)Imbalance
edapp_description is highly imbalanced (93.9%)Imbalance
edapp_version is highly imbalanced (89.7%)Imbalance
referrer_extensions_assignmentsemester is highly imbalanced (75.2%)Imbalance
referrer_extensions_assignmentmchapter is highly imbalanced (79.4%)Imbalance
referrer_extensions_assignmentprogday_kst is highly imbalanced (56.6%)Imbalance
extensions_timezone is highly imbalanced (98.4%)Imbalance
object_mediatype has 671 (100.0%) missing valuesMissing
object_learningobjectives has 671 (100.0%) missing valuesMissing
object_datetostarton has 316 (47.1%) missing valuesMissing
object_datetostarton_kst has 316 (47.1%) missing valuesMissing
object_datetosubmit has 467 (69.6%) missing valuesMissing
object_datetosubmit_kst has 467 (69.6%) missing valuesMissing
object_maxattempts has 671 (100.0%) missing valuesMissing
object_maxsubmits has 671 (100.0%) missing valuesMissing
object_maxscore has 671 (100.0%) missing valuesMissing
referrer_extensions_assignmentsemester has 90 (13.4%) missing valuesMissing
id is uniformly distributedUniform
eventtime_kst is uniformly distributedUniform
object_datetostarton_kst is uniformly distributedUniform
object_datetosubmit_kst is uniformly distributedUniform
in_datetime_kst is uniformly distributedUniform
in_datetime_kst has unique valuesUnique
object_mediatype is an unsupported type, check if it needs cleaning or further analysisUnsupported
object_learningobjectives is an unsupported type, check if it needs cleaning or further analysisUnsupported
object_maxattempts is an unsupported type, check if it needs cleaning or further analysisUnsupported
object_maxsubmits is an unsupported type, check if it needs cleaning or further analysisUnsupported
object_maxscore is an unsupported type, check if it needs cleaning or further analysisUnsupported
referrer_extensions_assignmentgrade has 473 (70.5%) zerosZeros

Reproduction

Analysis started2023-04-25 00:50:34.788571
Analysis finished2023-04-25 00:50:49.352026
Duration14.56 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

context
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://purl.imsglobal.org/ctx/caliper/v1p1
671 

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters28182
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://purl.imsglobal.org/ctx/caliper/v1p1
2nd rowhttp://purl.imsglobal.org/ctx/caliper/v1p1
3rd rowhttp://purl.imsglobal.org/ctx/caliper/v1p1
4th rowhttp://purl.imsglobal.org/ctx/caliper/v1p1
5th rowhttp://purl.imsglobal.org/ctx/caliper/v1p1

Common Values

ValueCountFrequency (%)
http://purl.imsglobal.org/ctx/caliper/v1p1 671
100.0%

Length

2023-04-25T09:50:49.426024image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:49.516287image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
http://purl.imsglobal.org/ctx/caliper/v1p1 671
100.0%

Most occurring characters

ValueCountFrequency (%)
/ 3355
 
11.9%
p 2684
 
9.5%
l 2684
 
9.5%
r 2013
 
7.1%
t 2013
 
7.1%
1 1342
 
4.8%
a 1342
 
4.8%
. 1342
 
4.8%
i 1342
 
4.8%
g 1342
 
4.8%
Other values (11) 8723
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21472
76.2%
Other Punctuation 5368
 
19.0%
Decimal Number 1342
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 2684
12.5%
l 2684
12.5%
r 2013
9.4%
t 2013
9.4%
a 1342
 
6.2%
i 1342
 
6.2%
g 1342
 
6.2%
o 1342
 
6.2%
c 1342
 
6.2%
v 671
 
3.1%
Other values (7) 4697
21.9%
Other Punctuation
ValueCountFrequency (%)
/ 3355
62.5%
. 1342
 
25.0%
: 671
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 1342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21472
76.2%
Common 6710
 
23.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2684
12.5%
l 2684
12.5%
r 2013
9.4%
t 2013
9.4%
a 1342
 
6.2%
i 1342
 
6.2%
g 1342
 
6.2%
o 1342
 
6.2%
c 1342
 
6.2%
v 671
 
3.1%
Other values (7) 4697
21.9%
Common
ValueCountFrequency (%)
/ 3355
50.0%
1 1342
 
20.0%
. 1342
 
20.0%
: 671
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 3355
 
11.9%
p 2684
 
9.5%
l 2684
 
9.5%
r 2013
 
7.1%
t 2013
 
7.1%
1 1342
 
4.8%
a 1342
 
4.8%
. 1342
 
4.8%
i 1342
 
4.8%
g 1342
 
4.8%
Other values (11) 8723
31.0%

id
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct667
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
urn:uuid:9000360c-3327-4f1f-be9a-a81d05c0d9f3
 
2
urn:uuid:058de100-e6d8-4de3-a32d-d462e976871e
 
2
urn:uuid:59b3aa4c-6f40-45c4-84f8-64ee4af7ec91
 
2
urn:uuid:1a0af767-dc56-4912-9ed2-f6dc5bdb64f6
 
2
urn:uuid:690e96a0-a203-435b-b157-5737cf5a5c65
 
1
Other values (662)
662 

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters30195
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)98.8%

Sample

1st rowurn:uuid:690e96a0-a203-435b-b157-5737cf5a5c65
2nd rowurn:uuid:f7cdfdf0-fbcb-4766-b17b-34a63d79a2f4
3rd rowurn:uuid:6619a8b1-31b3-4ac9-8fa1-5a69fc9d6bac
4th rowurn:uuid:304daccd-0930-4060-99d5-81db499ac2e7
5th rowurn:uuid:2e94e401-ae0f-46bf-9057-f5751052b7f6

Common Values

ValueCountFrequency (%)
urn:uuid:9000360c-3327-4f1f-be9a-a81d05c0d9f3 2
 
0.3%
urn:uuid:058de100-e6d8-4de3-a32d-d462e976871e 2
 
0.3%
urn:uuid:59b3aa4c-6f40-45c4-84f8-64ee4af7ec91 2
 
0.3%
urn:uuid:1a0af767-dc56-4912-9ed2-f6dc5bdb64f6 2
 
0.3%
urn:uuid:690e96a0-a203-435b-b157-5737cf5a5c65 1
 
0.1%
urn:uuid:91e3dbf1-4a41-4e21-a4d9-23d2dba9f523 1
 
0.1%
urn:uuid:1023abaa-dd3b-4c1a-a393-abade2c7c048 1
 
0.1%
urn:uuid:5c84aca0-0134-43bf-9d65-3d9d64387464 1
 
0.1%
urn:uuid:d0835bd4-6ab9-484c-9a74-81ce2e6eae5d 1
 
0.1%
urn:uuid:305e7670-db28-481d-a697-8599f750e903 1
 
0.1%
Other values (657) 657
97.9%

Length

2023-04-25T09:50:49.578788image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
urn:uuid:9000360c-3327-4f1f-be9a-a81d05c0d9f3 2
 
0.3%
urn:uuid:59b3aa4c-6f40-45c4-84f8-64ee4af7ec91 2
 
0.3%
urn:uuid:1a0af767-dc56-4912-9ed2-f6dc5bdb64f6 2
 
0.3%
urn:uuid:058de100-e6d8-4de3-a32d-d462e976871e 2
 
0.3%
urn:uuid:0b9af0c3-b7e6-4da3-9e00-6cad690f6699 1
 
0.1%
urn:uuid:14780b6a-6f87-4f57-8264-37a387d09525 1
 
0.1%
urn:uuid:6619a8b1-31b3-4ac9-8fa1-5a69fc9d6bac 1
 
0.1%
urn:uuid:304daccd-0930-4060-99d5-81db499ac2e7 1
 
0.1%
urn:uuid:2e94e401-ae0f-46bf-9057-f5751052b7f6 1
 
0.1%
urn:uuid:03379bb6-5ee7-4232-9702-4c30afc172c8 1
 
0.1%
Other values (657) 657
97.9%

Most occurring characters

ValueCountFrequency (%)
- 2684
 
8.9%
u 2013
 
6.7%
d 2000
 
6.6%
4 1935
 
6.4%
8 1447
 
4.8%
b 1420
 
4.7%
9 1418
 
4.7%
a 1408
 
4.7%
: 1342
 
4.4%
6 1301
 
4.3%
Other values (12) 13227
43.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13609
45.1%
Lowercase Letter 12560
41.6%
Dash Punctuation 2684
 
8.9%
Other Punctuation 1342
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 2013
16.0%
d 2000
15.9%
b 1420
11.3%
a 1408
11.2%
c 1262
10.0%
e 1225
9.8%
f 1219
9.7%
r 671
 
5.3%
i 671
 
5.3%
n 671
 
5.3%
Decimal Number
ValueCountFrequency (%)
4 1935
14.2%
8 1447
10.6%
9 1418
10.4%
6 1301
9.6%
3 1275
9.4%
5 1257
9.2%
2 1247
9.2%
0 1247
9.2%
7 1245
9.1%
1 1237
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 2684
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17635
58.4%
Latin 12560
41.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2684
15.2%
4 1935
11.0%
8 1447
8.2%
9 1418
8.0%
: 1342
7.6%
6 1301
7.4%
3 1275
7.2%
5 1257
7.1%
2 1247
7.1%
0 1247
7.1%
Other values (2) 2482
14.1%
Latin
ValueCountFrequency (%)
u 2013
16.0%
d 2000
15.9%
b 1420
11.3%
a 1408
11.2%
c 1262
10.0%
e 1225
9.8%
f 1219
9.7%
r 671
 
5.3%
i 671
 
5.3%
n 671
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2684
 
8.9%
u 2013
 
6.7%
d 2000
 
6.6%
4 1935
 
6.4%
8 1447
 
4.8%
b 1420
 
4.7%
9 1418
 
4.7%
a 1408
 
4.7%
: 1342
 
4.4%
6 1301
 
4.3%
Other values (12) 13227
43.8%

type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
AssignableEvent
671 

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters10065
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAssignableEvent
2nd rowAssignableEvent
3rd rowAssignableEvent
4th rowAssignableEvent
5th rowAssignableEvent

Common Values

ValueCountFrequency (%)
AssignableEvent 671
100.0%

Length

2023-04-25T09:50:49.672538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:49.735041image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
assignableevent 671
100.0%

Most occurring characters

ValueCountFrequency (%)
s 1342
13.3%
n 1342
13.3%
e 1342
13.3%
A 671
6.7%
i 671
6.7%
g 671
6.7%
a 671
6.7%
b 671
6.7%
l 671
6.7%
E 671
6.7%
Other values (2) 1342
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8723
86.7%
Uppercase Letter 1342
 
13.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1342
15.4%
n 1342
15.4%
e 1342
15.4%
i 671
7.7%
g 671
7.7%
a 671
7.7%
b 671
7.7%
l 671
7.7%
v 671
7.7%
t 671
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 671
50.0%
E 671
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10065
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1342
13.3%
n 1342
13.3%
e 1342
13.3%
A 671
6.7%
i 671
6.7%
g 671
6.7%
a 671
6.7%
b 671
6.7%
l 671
6.7%
E 671
6.7%
Other values (2) 1342
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10065
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 1342
13.3%
n 1342
13.3%
e 1342
13.3%
A 671
6.7%
i 671
6.7%
g 671
6.7%
a 671
6.7%
b 671
6.7%
l 671
6.7%
E 671
6.7%
Other values (2) 1342
13.3%

actor_id
Categorical

Distinct285
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969e
 
9
http://app.milkt.co.kr/person/c75dde42-07ed-4ddf-9019-fff78f8cbe5b
 
9
http://app.milkt.co.kr/person/df4a9b9a-be9e-4d79-bd4e-3effb3637ebb
 
8
http://app.milkt.co.kr/person/21d2dd54-7d32-4191-af39-b5090b530c8b
 
8
http://app.milkt.co.kr/person/b1b2227f-e294-454d-8547-2ce898b36a9b
 
8
Other values (280)
629 

Length

Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

Total characters44286
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)16.1%

Sample

1st rowhttp://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969e
2nd rowhttp://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969e
3rd rowhttp://app.milkt.co.kr/person/3671dfaf-bfe9-4e10-8b76-283d6b38365d
4th rowhttp://app.milkt.co.kr/person/e187203e-cced-4b3b-b6ed-80d607013b9d
5th rowhttp://app.milkt.co.kr/person/86f941d5-14a9-4bc2-a48b-a54649e14b4f

Common Values

ValueCountFrequency (%)
http://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969e 9
 
1.3%
http://app.milkt.co.kr/person/c75dde42-07ed-4ddf-9019-fff78f8cbe5b 9
 
1.3%
http://app.milkt.co.kr/person/df4a9b9a-be9e-4d79-bd4e-3effb3637ebb 8
 
1.2%
http://app.milkt.co.kr/person/21d2dd54-7d32-4191-af39-b5090b530c8b 8
 
1.2%
http://app.milkt.co.kr/person/b1b2227f-e294-454d-8547-2ce898b36a9b 8
 
1.2%
http://app.milkt.co.kr/person/26478421-08b0-4270-ac38-8dd477e1f4cd 7
 
1.0%
http://app.milkt.co.kr/person/b29e9674-8262-4cdc-b666-d2b4b9dd4405 7
 
1.0%
http://app.milkt.co.kr/person/ce89333d-6d7e-4a13-a41b-9e8f5b04619a 7
 
1.0%
http://app.milkt.co.kr/person/4ef96173-0950-4ebd-a848-7653421d6bc2 6
 
0.9%
http://app.milkt.co.kr/person/d4dc9d1b-5088-45c1-8e79-048f81361672 6
 
0.9%
Other values (275) 596
88.8%

Length

2023-04-25T09:50:49.797548image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969e 9
 
1.3%
http://app.milkt.co.kr/person/c75dde42-07ed-4ddf-9019-fff78f8cbe5b 9
 
1.3%
http://app.milkt.co.kr/person/df4a9b9a-be9e-4d79-bd4e-3effb3637ebb 8
 
1.2%
http://app.milkt.co.kr/person/21d2dd54-7d32-4191-af39-b5090b530c8b 8
 
1.2%
http://app.milkt.co.kr/person/b1b2227f-e294-454d-8547-2ce898b36a9b 8
 
1.2%
http://app.milkt.co.kr/person/26478421-08b0-4270-ac38-8dd477e1f4cd 7
 
1.0%
http://app.milkt.co.kr/person/b29e9674-8262-4cdc-b666-d2b4b9dd4405 7
 
1.0%
http://app.milkt.co.kr/person/ce89333d-6d7e-4a13-a41b-9e8f5b04619a 7
 
1.0%
http://app.milkt.co.kr/person/6412ad1b-1180-4ef5-bc71-5287aa7a0948 6
 
0.9%
http://app.milkt.co.kr/person/55390c83-0ee1-4e1e-9011-3c05b5a98e4b 6
 
0.9%
Other values (275) 596
88.8%

Most occurring characters

ValueCountFrequency (%)
- 2684
 
6.1%
p 2684
 
6.1%
/ 2684
 
6.1%
4 2048
 
4.6%
. 2013
 
4.5%
t 2013
 
4.5%
a 1975
 
4.5%
c 1964
 
4.4%
e 1955
 
4.4%
b 1454
 
3.3%
Other values (21) 22812
51.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22712
51.3%
Decimal Number 13522
30.5%
Other Punctuation 5368
 
12.1%
Dash Punctuation 2684
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 2684
11.8%
t 2013
 
8.9%
a 1975
 
8.7%
c 1964
 
8.6%
e 1955
 
8.6%
b 1454
 
6.4%
d 1389
 
6.1%
r 1342
 
5.9%
k 1342
 
5.9%
o 1342
 
5.9%
Other values (7) 5252
23.1%
Decimal Number
ValueCountFrequency (%)
4 2048
15.1%
9 1436
10.6%
8 1394
10.3%
1 1338
9.9%
0 1309
9.7%
3 1305
9.7%
6 1219
9.0%
2 1185
8.8%
5 1145
8.5%
7 1143
8.5%
Other Punctuation
ValueCountFrequency (%)
/ 2684
50.0%
. 2013
37.5%
: 671
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 2684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22712
51.3%
Common 21574
48.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2684
11.8%
t 2013
 
8.9%
a 1975
 
8.7%
c 1964
 
8.6%
e 1955
 
8.6%
b 1454
 
6.4%
d 1389
 
6.1%
r 1342
 
5.9%
k 1342
 
5.9%
o 1342
 
5.9%
Other values (7) 5252
23.1%
Common
ValueCountFrequency (%)
- 2684
12.4%
/ 2684
12.4%
4 2048
9.5%
. 2013
9.3%
9 1436
 
6.7%
8 1394
 
6.5%
1 1338
 
6.2%
0 1309
 
6.1%
3 1305
 
6.0%
6 1219
 
5.7%
Other values (4) 4144
19.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2684
 
6.1%
p 2684
 
6.1%
/ 2684
 
6.1%
4 2048
 
4.6%
. 2013
 
4.5%
t 2013
 
4.5%
a 1975
 
4.5%
c 1964
 
4.4%
e 1955
 
4.4%
b 1454
 
3.3%
Other values (21) 22812
51.5%

actor_type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Person
671 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters4026
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPerson
2nd rowPerson
3rd rowPerson
4th rowPerson
5th rowPerson

Common Values

ValueCountFrequency (%)
Person 671
100.0%

Length

2023-04-25T09:50:49.891288image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:49.969412image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
person 671
100.0%

Most occurring characters

ValueCountFrequency (%)
P 671
16.7%
e 671
16.7%
r 671
16.7%
s 671
16.7%
o 671
16.7%
n 671
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3355
83.3%
Uppercase Letter 671
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 671
20.0%
r 671
20.0%
s 671
20.0%
o 671
20.0%
n 671
20.0%
Uppercase Letter
ValueCountFrequency (%)
P 671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4026
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 671
16.7%
e 671
16.7%
r 671
16.7%
s 671
16.7%
o 671
16.7%
n 671
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 671
16.7%
e 671
16.7%
r 671
16.7%
s 671
16.7%
o 671
16.7%
n 671
16.7%
Distinct285
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
leeso0215
 
9
mingi0828
 
9
psh1026
 
8
seonho0609
 
8
sunu0528
 
8
Other values (280)
629 

Length

Max length13
Median length11
Mean length8.3457526
Min length5

Characters and Unicode

Total characters5600
Distinct characters60
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)16.1%

Sample

1st rowleeso0215
2nd rowleeso0215
3rd rowlisjm1
4th rowtnwjd8209
5th rowsws0324

Common Values

ValueCountFrequency (%)
leeso0215 9
 
1.3%
mingi0828 9
 
1.3%
psh1026 8
 
1.2%
seonho0609 8
 
1.2%
sunu0528 8
 
1.2%
Ian0415 7
 
1.0%
P20171202 7
 
1.0%
Jaeha0331 7
 
1.0%
cosua1010 6
 
0.9%
Seoa170331 6
 
0.9%
Other values (275) 596
88.8%

Length

2023-04-25T09:50:50.031917image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
leeso0215 9
 
1.3%
mingi0828 9
 
1.3%
psh1026 8
 
1.2%
seonho0609 8
 
1.2%
sunu0528 8
 
1.2%
ian0415 7
 
1.0%
p20171202 7
 
1.0%
jaeha0331 7
 
1.0%
sojeong1108 6
 
0.9%
yunshu 6
 
0.9%
Other values (275) 596
88.8%

Most occurring characters

ValueCountFrequency (%)
0 528
 
9.4%
1 516
 
9.2%
2 327
 
5.8%
o 270
 
4.8%
n 255
 
4.6%
a 240
 
4.3%
7 230
 
4.1%
s 220
 
3.9%
e 211
 
3.8%
i 195
 
3.5%
Other values (50) 2608
46.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2863
51.1%
Decimal Number 2496
44.6%
Uppercase Letter 241
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 270
 
9.4%
n 255
 
8.9%
a 240
 
8.4%
s 220
 
7.7%
e 211
 
7.4%
i 195
 
6.8%
h 160
 
5.6%
u 145
 
5.1%
j 141
 
4.9%
y 132
 
4.6%
Other values (16) 894
31.2%
Uppercase Letter
ValueCountFrequency (%)
J 32
13.3%
Y 19
 
7.9%
S 18
 
7.5%
L 17
 
7.1%
D 16
 
6.6%
H 13
 
5.4%
O 13
 
5.4%
N 12
 
5.0%
M 12
 
5.0%
P 11
 
4.6%
Other values (14) 78
32.4%
Decimal Number
ValueCountFrequency (%)
0 528
21.2%
1 516
20.7%
2 327
13.1%
7 230
9.2%
8 188
 
7.5%
3 167
 
6.7%
6 146
 
5.8%
9 144
 
5.8%
4 127
 
5.1%
5 123
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 3104
55.4%
Common 2496
44.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 270
 
8.7%
n 255
 
8.2%
a 240
 
7.7%
s 220
 
7.1%
e 211
 
6.8%
i 195
 
6.3%
h 160
 
5.2%
u 145
 
4.7%
j 141
 
4.5%
y 132
 
4.3%
Other values (40) 1135
36.6%
Common
ValueCountFrequency (%)
0 528
21.2%
1 516
20.7%
2 327
13.1%
7 230
9.2%
8 188
 
7.5%
3 167
 
6.7%
6 146
 
5.8%
9 144
 
5.8%
4 127
 
5.1%
5 123
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 528
 
9.4%
1 516
 
9.2%
2 327
 
5.8%
o 270
 
4.8%
n 255
 
4.6%
a 240
 
4.3%
7 230
 
4.1%
s 220
 
3.9%
e 211
 
3.8%
i 195
 
3.5%
Other values (50) 2608
46.6%

actor_extensions_usertype
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
11
618 
01
 
53

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1342
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row01

Common Values

ValueCountFrequency (%)
11 618
92.1%
01 53
 
7.9%

Length

2023-04-25T09:50:50.125663image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:50.203788image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
11 618
92.1%
01 53
 
7.9%

Most occurring characters

ValueCountFrequency (%)
1 1289
96.1%
0 53
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1342
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1289
96.1%
0 53
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1342
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1289
96.1%
0 53
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1289
96.1%
0 53
 
3.9%

actor_extensions_usertypename
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
학습생(정)
618 
학습생(준)
 
53

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters4026
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row학습생(정)
2nd row학습생(정)
3rd row학습생(정)
4th row학습생(정)
5th row학습생(준)

Common Values

ValueCountFrequency (%)
학습생(정) 618
92.1%
학습생(준) 53
 
7.9%

Length

2023-04-25T09:50:50.250659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:50.342601image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
학습생(정 618
92.1%
학습생(준 53
 
7.9%

Most occurring characters

ValueCountFrequency (%)
671
16.7%
671
16.7%
671
16.7%
( 671
16.7%
) 671
16.7%
618
15.4%
53
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2684
66.7%
Open Punctuation 671
 
16.7%
Close Punctuation 671
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
671
25.0%
671
25.0%
671
25.0%
618
23.0%
53
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 671
100.0%
Close Punctuation
ValueCountFrequency (%)
) 671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2684
66.7%
Common 1342
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
671
25.0%
671
25.0%
671
25.0%
618
23.0%
53
 
2.0%
Common
ValueCountFrequency (%)
( 671
50.0%
) 671
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2684
66.7%
ASCII 1342
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
671
25.0%
671
25.0%
671
25.0%
618
23.0%
53
 
2.0%
ASCII
ValueCountFrequency (%)
( 671
50.0%
) 671
50.0%

actor_extensions_usertypedescription
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
정상적인 결제를 거친 학습생
618 
준회원세분-무료체험이 들어간 회원
 
53

Length

Max length18
Median length15
Mean length15.23696
Min length15

Characters and Unicode

Total characters10224
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상적인 결제를 거친 학습생
2nd row정상적인 결제를 거친 학습생
3rd row정상적인 결제를 거친 학습생
4th row정상적인 결제를 거친 학습생
5th row준회원세분-무료체험이 들어간 회원

Common Values

ValueCountFrequency (%)
정상적인 결제를 거친 학습생 618
92.1%
준회원세분-무료체험이 들어간 회원 53
 
7.9%

Length

2023-04-25T09:50:50.412598image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:50.511863image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
정상적인 618
23.5%
결제를 618
23.5%
거친 618
23.5%
학습생 618
23.5%
준회원세분-무료체험이 53
 
2.0%
들어간 53
 
2.0%
회원 53
 
2.0%

Most occurring characters

ValueCountFrequency (%)
1960
19.2%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
618
 
6.0%
Other values (17) 2702
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8211
80.3%
Space Separator 1960
 
19.2%
Dash Punctuation 53
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
Other values (15) 2031
24.7%
Space Separator
ValueCountFrequency (%)
1960
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8211
80.3%
Common 2013
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
Other values (15) 2031
24.7%
Common
ValueCountFrequency (%)
1960
97.4%
- 53
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8211
80.3%
ASCII 2013
 
19.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1960
97.4%
- 53
 
2.6%
Hangul
ValueCountFrequency (%)
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
618
 
7.5%
Other values (15) 2031
24.7%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
480 
초등
191 

Length

Max length2
Median length0
Mean length0.56929955
Min length0

Characters and Unicode

Total characters382
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
480
71.5%
초등 191
 
28.5%

Length

2023-04-25T09:50:50.586913image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:50.665243image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
초등 191
100.0%

Most occurring characters

ValueCountFrequency (%)
191
50.0%
191
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
191
50.0%
191
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
191
50.0%
191
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
191
50.0%
191
50.0%
Distinct7
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
480 
2학년
 
41
3학년
 
40
1학년
 
39
4학년
 
28
Other values (2)
 
43

Length

Max length3
Median length0
Mean length0.85394933
Min length0

Characters and Unicode

Total characters573
Distinct characters8
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
480
71.5%
2학년 41
 
6.1%
3학년 40
 
6.0%
1학년 39
 
5.8%
4학년 28
 
4.2%
5학년 28
 
4.2%
6학년 15
 
2.2%

Length

2023-04-25T09:50:50.730245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:50.817838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
2학년 41
21.5%
3학년 40
20.9%
1학년 39
20.4%
4학년 28
14.7%
5학년 28
14.7%
6학년 15
 
7.9%

Most occurring characters

ValueCountFrequency (%)
191
33.3%
191
33.3%
2 41
 
7.2%
3 40
 
7.0%
1 39
 
6.8%
4 28
 
4.9%
5 28
 
4.9%
6 15
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
66.7%
Decimal Number 191
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 41
21.5%
3 40
20.9%
1 39
20.4%
4 28
14.7%
5 28
14.7%
6 15
 
7.9%
Other Letter
ValueCountFrequency (%)
191
50.0%
191
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
66.7%
Common 191
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 41
21.5%
3 40
20.9%
1 39
20.4%
4 28
14.7%
5 28
14.7%
6 15
 
7.9%
Hangul
ValueCountFrequency (%)
191
50.0%
191
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
66.7%
ASCII 191
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
191
50.0%
191
50.0%
ASCII
ValueCountFrequency (%)
2 41
21.5%
3 40
20.9%
1 39
20.4%
4 28
14.7%
5 28
14.7%
6 15
 
7.9%

actor_extensions_userpost
Real number (ℝ)

Distinct268
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29462.705
Minimum1105
Maximum164426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-04-25T09:50:50.919513image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1105
5-th percentile6163.5
Q114049
median22394
Q344240
95-th percentile61203
Maximum164426
Range163321
Interquartile range (IQR)30191

Descriptive statistics

Standard deviation20661.373
Coefficient of variation (CV)0.7012721
Kurtosis8.9682559
Mean29462.705
Median Absolute Deviation (MAD)12097
Skewness1.8713095
Sum19769475
Variance4.2689233 × 108
MonotonicityNot monotonic
2023-04-25T09:50:51.013253image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15017 9
 
1.3%
51125 9
 
1.3%
54399 8
 
1.2%
25621 8
 
1.2%
58015 8
 
1.2%
57767 7
 
1.0%
16713 7
 
1.0%
11722 7
 
1.0%
18613 7
 
1.0%
17886 6
 
0.9%
Other values (258) 595
88.7%
ValueCountFrequency (%)
1105 1
 
0.1%
1335 3
0.4%
2043 3
0.4%
2080 1
 
0.1%
2084 1
 
0.1%
2255 4
0.6%
2467 1
 
0.1%
2762 3
0.4%
2794 2
0.3%
2798 2
0.3%
ValueCountFrequency (%)
164426 4
0.6%
63610 2
 
0.3%
63234 1
 
0.1%
63229 2
 
0.3%
63201 1
 
0.1%
62434 5
0.7%
62250 5
0.7%
62249 1
 
0.1%
62012 4
0.6%
62011 3
0.4%
Distinct158
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
mteacher6450
 
19
mteacher6508
 
17
mteacher6575r
 
16
mteacher5753
 
15
mteacher7224
 
14
Other values (153)
590 

Length

Max length13
Median length12
Mean length11.90462
Min length6

Characters and Unicode

Total characters7988
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)5.5%

Sample

1st rowmteacher7004
2nd rowmteacher7004
3rd rowmteacher7219
4th rowmteacher7224
5th rowmteacher6115

Common Values

ValueCountFrequency (%)
mteacher6450 19
 
2.8%
mteacher6508 17
 
2.5%
mteacher6575r 16
 
2.4%
mteacher5753 15
 
2.2%
mteacher7224 14
 
2.1%
mteacher6463 13
 
1.9%
mteacher6495 12
 
1.8%
mteacher5701 11
 
1.6%
mteacher6645 11
 
1.6%
mteacher6424 11
 
1.6%
Other values (148) 532
79.3%

Length

2023-04-25T09:50:51.122625image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mteacher6450 19
 
2.8%
mteacher6508 17
 
2.5%
mteacher6575r 16
 
2.4%
mteacher5753 15
 
2.2%
mteacher7224 14
 
2.1%
mteacher6463 13
 
1.9%
mteacher6495 12
 
1.8%
mteacher6424 11
 
1.6%
mteacher6225 11
 
1.6%
mteacher6645 11
 
1.6%
Other values (148) 532
79.3%

Most occurring characters

ValueCountFrequency (%)
e 1312
16.4%
r 680
8.5%
m 671
8.4%
t 671
8.4%
a 656
8.2%
c 656
8.2%
h 656
8.2%
6 538
6.7%
5 524
 
6.6%
7 280
 
3.5%
Other values (7) 1344
16.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5302
66.4%
Decimal Number 2686
33.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 538
20.0%
5 524
19.5%
7 280
10.4%
2 265
9.9%
4 219
8.2%
0 195
 
7.3%
8 191
 
7.1%
3 189
 
7.0%
9 154
 
5.7%
1 131
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 1312
24.7%
r 680
12.8%
m 671
12.7%
t 671
12.7%
a 656
12.4%
c 656
12.4%
h 656
12.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 5302
66.4%
Common 2686
33.6%

Most frequent character per script

Common
ValueCountFrequency (%)
6 538
20.0%
5 524
19.5%
7 280
10.4%
2 265
9.9%
4 219
8.2%
0 195
 
7.3%
8 191
 
7.1%
3 189
 
7.0%
9 154
 
5.7%
1 131
 
4.9%
Latin
ValueCountFrequency (%)
e 1312
24.7%
r 680
12.8%
m 671
12.7%
t 671
12.7%
a 656
12.4%
c 656
12.4%
h 656
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7988
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1312
16.4%
r 680
8.5%
m 671
8.4%
t 671
8.4%
a 656
8.2%
c 656
8.2%
h 656
8.2%
6 538
6.7%
5 524
 
6.6%
7 280
 
3.5%
Other values (7) 1344
16.8%
Distinct123
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
370 
coolk2m
 
9
joosulki
 
8
selly90
 
7
lca8031
 
7
Other values (118)
270 

Length

Max length12
Median length0
Mean length3.7600596
Min length0

Characters and Unicode

Total characters2523
Distinct characters38
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)6.3%

Sample

1st rowcoolk2m
2nd rowcoolk2m
3rd row
4th row
5th rowsiruyo

Common Values

ValueCountFrequency (%)
370
55.1%
coolk2m 9
 
1.3%
joosulki 8
 
1.2%
selly90 7
 
1.0%
lca8031 7
 
1.0%
ian170415 7
 
1.0%
dutlthdbsl 6
 
0.9%
rosaria53 6
 
0.9%
Joonmin0527 5
 
0.7%
ghdlghdl777 5
 
0.7%
Other values (113) 241
35.9%

Length

2023-04-25T09:50:51.336648image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
coolk2m 9
 
3.0%
joosulki 8
 
2.7%
selly90 7
 
2.3%
lca8031 7
 
2.3%
ian170415 7
 
2.3%
dutlthdbsl 6
 
2.0%
rosaria53 6
 
2.0%
jjung68588 5
 
1.7%
siruyo 5
 
1.7%
joyjuy 5
 
1.7%
Other values (112) 236
78.4%

Most occurring characters

ValueCountFrequency (%)
o 147
 
5.8%
s 128
 
5.1%
0 125
 
5.0%
e 125
 
5.0%
n 123
 
4.9%
l 122
 
4.8%
1 121
 
4.8%
a 120
 
4.8%
i 104
 
4.1%
u 98
 
3.9%
Other values (28) 1310
51.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1764
69.9%
Decimal Number 749
29.7%
Uppercase Letter 10
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 147
 
8.3%
s 128
 
7.3%
e 125
 
7.1%
n 123
 
7.0%
l 122
 
6.9%
a 120
 
6.8%
i 104
 
5.9%
u 98
 
5.6%
y 96
 
5.4%
d 83
 
4.7%
Other values (15) 618
35.0%
Decimal Number
ValueCountFrequency (%)
0 125
16.7%
1 121
16.2%
2 91
12.1%
8 78
10.4%
7 66
8.8%
9 63
8.4%
5 61
8.1%
3 53
7.1%
6 52
6.9%
4 39
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
J 6
60.0%
A 3
30.0%
E 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1774
70.3%
Common 749
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 147
 
8.3%
s 128
 
7.2%
e 125
 
7.0%
n 123
 
6.9%
l 122
 
6.9%
a 120
 
6.8%
i 104
 
5.9%
u 98
 
5.5%
y 96
 
5.4%
d 83
 
4.7%
Other values (18) 628
35.4%
Common
ValueCountFrequency (%)
0 125
16.7%
1 121
16.2%
2 91
12.1%
8 78
10.4%
7 66
8.8%
9 63
8.4%
5 61
8.1%
3 53
7.1%
6 52
6.9%
4 39
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 147
 
5.8%
s 128
 
5.1%
0 125
 
5.0%
e 125
 
5.0%
n 123
 
4.9%
l 122
 
4.8%
1 121
 
4.8%
a 120
 
4.8%
i 104
 
4.1%
u 98
 
3.9%
Other values (28) 1310
51.9%

action
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Started
286 
Submitted
204 
Completed
151 
Reviewed
30 

Length

Max length9
Median length9
Mean length8.1028316
Min length7

Characters and Unicode

Total characters5437
Distinct characters17
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSubmitted
2nd rowCompleted
3rd rowCompleted
4th rowStarted
5th rowSubmitted

Common Values

ValueCountFrequency (%)
Started 286
42.6%
Submitted 204
30.4%
Completed 151
22.5%
Reviewed 30
 
4.5%

Length

2023-04-25T09:50:51.465650image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:51.553590image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
started 286
42.6%
submitted 204
30.4%
completed 151
22.5%
reviewed 30
 
4.5%

Most occurring characters

ValueCountFrequency (%)
t 1131
20.8%
e 882
16.2%
d 671
12.3%
S 490
9.0%
m 355
 
6.5%
r 286
 
5.3%
a 286
 
5.3%
i 234
 
4.3%
u 204
 
3.8%
b 204
 
3.8%
Other values (7) 694
12.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4766
87.7%
Uppercase Letter 671
 
12.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1131
23.7%
e 882
18.5%
d 671
14.1%
m 355
 
7.4%
r 286
 
6.0%
a 286
 
6.0%
i 234
 
4.9%
u 204
 
4.3%
b 204
 
4.3%
o 151
 
3.2%
Other values (4) 362
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
S 490
73.0%
C 151
 
22.5%
R 30
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 5437
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1131
20.8%
e 882
16.2%
d 671
12.3%
S 490
9.0%
m 355
 
6.5%
r 286
 
5.3%
a 286
 
5.3%
i 234
 
4.3%
u 204
 
3.8%
b 204
 
3.8%
Other values (7) 694
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1131
20.8%
e 882
16.2%
d 671
12.3%
S 490
9.0%
m 355
 
6.5%
r 286
 
5.3%
a 286
 
5.3%
i 234
 
4.3%
u 204
 
3.8%
b 204
 
3.8%
Other values (7) 694
12.8%
Distinct667
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2023-03-11 08:56:24.964000
Maximum2023-04-05 22:46:01.225000
2023-04-25T09:50:51.671392image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:51.798391image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

eventtime_kst
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct667
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-04-06 07:15:00.498000
 
2
2023-04-06 07:23:22.367000
 
2
2023-04-06 07:05:30.715000
 
2
2023-04-06 07:29:49.759000
 
2
2023-04-06 07:31:01.174000
 
1
Other values (662)
662 

Length

Max length26
Median length26
Mean length25.989568
Min length19

Characters and Unicode

Total characters17439
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)98.8%

Sample

1st row2023-04-06 07:31:01.174000
2nd row2023-04-06 07:31:01.188000
3rd row2023-04-06 07:31:00.765000
4th row2023-04-06 07:31:07.456000
5th row2023-04-06 07:31:05.786000

Common Values

ValueCountFrequency (%)
2023-04-06 07:15:00.498000 2
 
0.3%
2023-04-06 07:23:22.367000 2
 
0.3%
2023-04-06 07:05:30.715000 2
 
0.3%
2023-04-06 07:29:49.759000 2
 
0.3%
2023-04-06 07:31:01.174000 1
 
0.1%
2023-04-06 07:41:10.008000 1
 
0.1%
2023-04-06 07:37:55.814000 1
 
0.1%
2023-04-06 07:41:10.099000 1
 
0.1%
2023-04-06 07:41:09.040000 1
 
0.1%
2023-04-06 07:41:13.215000 1
 
0.1%
Other values (657) 657
97.9%

Length

2023-04-25T09:50:51.901502image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-04-06 644
48.0%
2023-04-05 14
 
1.0%
2023-03-22 4
 
0.3%
2023-03-18 4
 
0.3%
2023-03-17 3
 
0.2%
07:23:22.367000 2
 
0.1%
07:05:30.715000 2
 
0.1%
07:29:49.759000 2
 
0.1%
07:15:00.498000 2
 
0.1%
07:31:11.505000 1
 
0.1%
Other values (664) 664
49.5%

Most occurring characters

ValueCountFrequency (%)
0 5076
29.1%
2 1824
 
10.5%
3 1569
 
9.0%
4 1356
 
7.8%
- 1342
 
7.7%
: 1342
 
7.7%
7 993
 
5.7%
6 951
 
5.5%
671
 
3.8%
. 670
 
3.8%
Other values (4) 1645
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13414
76.9%
Other Punctuation 2012
 
11.5%
Dash Punctuation 1342
 
7.7%
Space Separator 671
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5076
37.8%
2 1824
 
13.6%
3 1569
 
11.7%
4 1356
 
10.1%
7 993
 
7.4%
6 951
 
7.1%
5 507
 
3.8%
1 479
 
3.6%
8 354
 
2.6%
9 305
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 1342
66.7%
. 670
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1342
100.0%
Space Separator
ValueCountFrequency (%)
671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17439
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5076
29.1%
2 1824
 
10.5%
3 1569
 
9.0%
4 1356
 
7.8%
- 1342
 
7.7%
: 1342
 
7.7%
7 993
 
5.7%
6 951
 
5.5%
671
 
3.8%
. 670
 
3.8%
Other values (4) 1645
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5076
29.1%
2 1824
 
10.5%
3 1569
 
9.0%
4 1356
 
7.8%
- 1342
 
7.7%
: 1342
 
7.7%
7 993
 
5.7%
6 951
 
5.5%
671
 
3.8%
. 670
 
3.8%
Other values (4) 1645
 
9.4%

object_id
Categorical

Distinct234
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://app.milkt.co.kr/T0VE01U06003
86 
http://app.milkt.co.kr/T0ME01U12010
 
40
http://app.milkt.co.kr/T0ME01U05010
 
33
http://app.milkt.co.kr/T0ME01U04010
 
17
http://app.milkt.co.kr/T0BE00U24006
 
17
Other values (229)
478 

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters23485
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)16.5%

Sample

1st rowhttp://app.milkt.co.kr/T0VE01U04009
2nd rowhttp://app.milkt.co.kr/T0VE01U04009
3rd rowhttp://app.milkt.co.kr/T0VE01U06003
4th rowhttp://app.milkt.co.kr/T0VE01U06003
5th rowhttp://app.milkt.co.kr/T0EE01U04008

Common Values

ValueCountFrequency (%)
http://app.milkt.co.kr/T0VE01U06003 86
 
12.8%
http://app.milkt.co.kr/T0ME01U12010 40
 
6.0%
http://app.milkt.co.kr/T0ME01U05010 33
 
4.9%
http://app.milkt.co.kr/T0ME01U04010 17
 
2.5%
http://app.milkt.co.kr/T0BE00U24006 17
 
2.5%
http://app.milkt.co.kr/T0VE01U05006 15
 
2.2%
http://app.milkt.co.kr/T0BE00U19006 15
 
2.2%
http://app.milkt.co.kr/T0EE01U05009 13
 
1.9%
http://app.milkt.co.kr/T0VE01U02004 13
 
1.9%
http://app.milkt.co.kr/T0VE01U01004 10
 
1.5%
Other values (224) 412
61.4%

Length

2023-04-25T09:50:52.018218image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://app.milkt.co.kr/t0ve01u06003 86
 
12.8%
http://app.milkt.co.kr/t0me01u12010 40
 
6.0%
http://app.milkt.co.kr/t0me01u05010 33
 
4.9%
http://app.milkt.co.kr/t0me01u04010 17
 
2.5%
http://app.milkt.co.kr/t0be00u24006 17
 
2.5%
http://app.milkt.co.kr/t0ve01u05006 15
 
2.2%
http://app.milkt.co.kr/t0be00u19006 15
 
2.2%
http://app.milkt.co.kr/t0ve01u02004 13
 
1.9%
http://app.milkt.co.kr/t0ee01u05009 13
 
1.9%
http://app.milkt.co.kr/t0ve01u01004 10
 
1.5%
Other values (224) 412
61.4%

Most occurring characters

ValueCountFrequency (%)
0 2911
 
12.4%
p 2013
 
8.6%
t 2013
 
8.6%
/ 2013
 
8.6%
. 2013
 
8.6%
k 1342
 
5.7%
1 973
 
4.1%
E 761
 
3.2%
U 672
 
2.9%
T 672
 
2.9%
Other values (35) 8102
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10736
45.7%
Decimal Number 5294
22.5%
Other Punctuation 4697
20.0%
Uppercase Letter 2758
 
11.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 761
27.6%
U 672
24.4%
T 672
24.4%
V 196
 
7.1%
M 158
 
5.7%
B 94
 
3.4%
K 54
 
2.0%
W 29
 
1.1%
A 24
 
0.9%
S 21
 
0.8%
Other values (11) 77
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
p 2013
18.8%
t 2013
18.8%
k 1342
12.5%
h 671
 
6.2%
r 671
 
6.2%
o 671
 
6.2%
c 671
 
6.2%
l 671
 
6.2%
i 671
 
6.2%
m 671
 
6.2%
Decimal Number
ValueCountFrequency (%)
0 2911
55.0%
1 973
 
18.4%
2 278
 
5.3%
3 261
 
4.9%
6 224
 
4.2%
4 180
 
3.4%
5 177
 
3.3%
9 134
 
2.5%
8 88
 
1.7%
7 68
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 2013
42.9%
. 2013
42.9%
: 671
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 13494
57.5%
Common 9991
42.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2013
14.9%
t 2013
14.9%
k 1342
9.9%
E 761
 
5.6%
U 672
 
5.0%
T 672
 
5.0%
h 671
 
5.0%
r 671
 
5.0%
o 671
 
5.0%
c 671
 
5.0%
Other values (22) 3337
24.7%
Common
ValueCountFrequency (%)
0 2911
29.1%
/ 2013
20.1%
. 2013
20.1%
1 973
 
9.7%
: 671
 
6.7%
2 278
 
2.8%
3 261
 
2.6%
6 224
 
2.2%
4 180
 
1.8%
5 177
 
1.8%
Other values (3) 290
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2911
 
12.4%
p 2013
 
8.6%
t 2013
 
8.6%
/ 2013
 
8.6%
. 2013
 
8.6%
k 1342
 
5.7%
1 973
 
4.1%
E 761
 
3.2%
U 672
 
2.9%
T 672
 
2.9%
Other values (35) 8102
34.5%

object_type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
AssignableDigitalResource
671 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters16775
Distinct characters16
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAssignableDigitalResource
2nd rowAssignableDigitalResource
3rd rowAssignableDigitalResource
4th rowAssignableDigitalResource
5th rowAssignableDigitalResource

Common Values

ValueCountFrequency (%)
AssignableDigitalResource 671
100.0%

Length

2023-04-25T09:50:52.096335image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:52.174472image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
assignabledigitalresource 671
100.0%

Most occurring characters

ValueCountFrequency (%)
s 2013
12.0%
i 2013
12.0%
e 2013
12.0%
g 1342
 
8.0%
a 1342
 
8.0%
l 1342
 
8.0%
A 671
 
4.0%
n 671
 
4.0%
b 671
 
4.0%
D 671
 
4.0%
Other values (6) 4026
24.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14762
88.0%
Uppercase Letter 2013
 
12.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2013
13.6%
i 2013
13.6%
e 2013
13.6%
g 1342
9.1%
a 1342
9.1%
l 1342
9.1%
n 671
 
4.5%
b 671
 
4.5%
t 671
 
4.5%
o 671
 
4.5%
Other values (3) 2013
13.6%
Uppercase Letter
ValueCountFrequency (%)
A 671
33.3%
D 671
33.3%
R 671
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 16775
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2013
12.0%
i 2013
12.0%
e 2013
12.0%
g 1342
 
8.0%
a 1342
 
8.0%
l 1342
 
8.0%
A 671
 
4.0%
n 671
 
4.0%
b 671
 
4.0%
D 671
 
4.0%
Other values (6) 4026
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2013
12.0%
i 2013
12.0%
e 2013
12.0%
g 1342
 
8.0%
a 1342
 
8.0%
l 1342
 
8.0%
A 671
 
4.0%
n 671
 
4.0%
b 671
 
4.0%
D 671
 
4.0%
Other values (6) 4026
24.0%

object_name
Categorical

Distinct232
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
추석빔 입고 동네 한 바퀴
85 
99까지 수의 차례를 알아봐요 (2)
 
38
몇 시 30분인지 알아봐요 (1)
 
33
AI 추천 게임(2)
 
19
진짜 친구
 
17
Other values (227)
479 

Length

Max length53
Median length35
Mean length17.078987
Min length2

Characters and Unicode

Total characters11460
Distinct characters485
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)16.5%

Sample

1st row누구의 발자국일까?
2nd row누구의 발자국일까?
3rd row추석빔 입고 동네 한 바퀴
4th row추석빔 입고 동네 한 바퀴
5th rowWrite Alphabet Gg

Common Values

ValueCountFrequency (%)
추석빔 입고 동네 한 바퀴 85
 
12.7%
99까지 수의 차례를 알아봐요 (2) 38
 
5.7%
몇 시 30분인지 알아봐요 (1) 33
 
4.9%
AI 추천 게임(2) 19
 
2.8%
진짜 친구 17
 
2.5%
비교해 봐요 (1) 17
 
2.5%
土 (흙 토) 15
 
2.2%
캥거루의 캉캉 카페 11
 
1.6%
복 타러 간 총각 10
 
1.5%
주말농장에 가는 길 8
 
1.2%
Other values (222) 418
62.3%

Length

2023-04-25T09:50:52.236963image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
추석빔 86
 
2.8%
동네 86
 
2.8%
86
 
2.8%
바퀴 86
 
2.8%
입고 86
 
2.8%
알아봐요 82
 
2.6%
1 68
 
2.2%
2 56
 
1.8%
ai 53
 
1.7%
수학 51
 
1.6%
Other values (626) 2375
76.2%

Most occurring characters

ValueCountFrequency (%)
2726
 
23.8%
) 227
 
2.0%
( 227
 
2.0%
205
 
1.8%
156
 
1.4%
156
 
1.4%
2 143
 
1.2%
133
 
1.2%
128
 
1.1%
122
 
1.1%
Other values (475) 7237
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6311
55.1%
Space Separator 2726
23.8%
Lowercase Letter 624
 
5.4%
Decimal Number 531
 
4.6%
Close Punctuation 301
 
2.6%
Open Punctuation 301
 
2.6%
Uppercase Letter 272
 
2.4%
Other Punctuation 120
 
1.0%
Dash Punctuation 103
 
0.9%
Other Number 97
 
0.8%
Other values (3) 74
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
205
 
3.2%
156
 
2.5%
156
 
2.5%
133
 
2.1%
128
 
2.0%
122
 
1.9%
110
 
1.7%
108
 
1.7%
108
 
1.7%
108
 
1.7%
Other values (392) 4977
78.9%
Lowercase Letter
ValueCountFrequency (%)
e 79
12.7%
a 76
12.2%
n 60
9.6%
t 59
9.5%
l 44
 
7.1%
h 41
 
6.6%
o 38
 
6.1%
s 35
 
5.6%
i 25
 
4.0%
r 25
 
4.0%
Other values (13) 142
22.8%
Uppercase Letter
ValueCountFrequency (%)
A 82
30.1%
I 65
23.9%
W 20
 
7.4%
C 16
 
5.9%
S 16
 
5.9%
B 11
 
4.0%
T 10
 
3.7%
L 9
 
3.3%
H 8
 
2.9%
G 7
 
2.6%
Other values (10) 28
 
10.3%
Decimal Number
ValueCountFrequency (%)
2 143
26.9%
1 107
20.2%
3 104
19.6%
9 87
16.4%
0 42
 
7.9%
4 21
 
4.0%
7 13
 
2.4%
8 7
 
1.3%
5 6
 
1.1%
6 1
 
0.2%
Other Number
ValueCountFrequency (%)
30
30.9%
25
25.8%
18
18.6%
9
 
9.3%
5
 
5.2%
4
 
4.1%
4
 
4.1%
2
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 43
35.8%
. 25
20.8%
! 25
20.8%
? 22
18.3%
: 4
 
3.3%
/ 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 227
75.4%
57
 
18.9%
] 15
 
5.0%
2
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 227
75.4%
57
 
18.9%
[ 15
 
5.0%
2
 
0.7%
Math Symbol
ValueCountFrequency (%)
> 24
41.4%
~ 19
32.8%
+ 14
24.1%
÷ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
2726
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Final Punctuation
ValueCountFrequency (%)
15
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6282
54.8%
Common 4253
37.1%
Latin 896
 
7.8%
Han 29
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
205
 
3.3%
156
 
2.5%
156
 
2.5%
133
 
2.1%
128
 
2.0%
122
 
1.9%
110
 
1.8%
108
 
1.7%
108
 
1.7%
108
 
1.7%
Other values (381) 4948
78.8%
Latin
ValueCountFrequency (%)
A 82
 
9.2%
e 79
 
8.8%
a 76
 
8.5%
I 65
 
7.3%
n 60
 
6.7%
t 59
 
6.6%
l 44
 
4.9%
h 41
 
4.6%
o 38
 
4.2%
s 35
 
3.9%
Other values (33) 317
35.4%
Common
ValueCountFrequency (%)
2726
64.1%
) 227
 
5.3%
( 227
 
5.3%
2 143
 
3.4%
1 107
 
2.5%
3 104
 
2.4%
- 103
 
2.4%
9 87
 
2.0%
57
 
1.3%
57
 
1.3%
Other values (30) 415
 
9.8%
Han
ValueCountFrequency (%)
15
51.7%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6256
54.6%
ASCII 4917
42.9%
None 119
 
1.0%
Enclosed Alphanum 97
 
0.8%
CJK 29
 
0.3%
Compat Jamo 26
 
0.2%
Punctuation 15
 
0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2726
55.4%
) 227
 
4.6%
( 227
 
4.6%
2 143
 
2.9%
1 107
 
2.2%
3 104
 
2.1%
- 103
 
2.1%
9 87
 
1.8%
A 82
 
1.7%
e 79
 
1.6%
Other values (58) 1032
 
21.0%
Hangul
ValueCountFrequency (%)
205
 
3.3%
156
 
2.5%
156
 
2.5%
133
 
2.1%
128
 
2.0%
122
 
2.0%
110
 
1.8%
108
 
1.7%
108
 
1.7%
108
 
1.7%
Other values (369) 4922
78.7%
None
ValueCountFrequency (%)
57
47.9%
57
47.9%
2
 
1.7%
2
 
1.7%
÷ 1
 
0.8%
Enclosed Alphanum
ValueCountFrequency (%)
30
30.9%
25
25.8%
18
18.6%
9
 
9.3%
5
 
5.2%
4
 
4.1%
4
 
4.1%
2
 
2.1%
Punctuation
ValueCountFrequency (%)
15
100.0%
CJK
ValueCountFrequency (%)
15
51.7%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Compat Jamo
ValueCountFrequency (%)
5
19.2%
3
11.5%
3
11.5%
3
11.5%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
Other values (2) 2
 
7.7%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%

object_mediatype
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing671
Missing (%)100.0%
Memory size5.4 KiB

object_learningobjectives
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing671
Missing (%)100.0%
Memory size5.4 KiB
Distinct277
Distinct (%)78.0%
Missing316
Missing (%)47.1%
Memory size5.4 KiB
Minimum2023-03-11 08:45:32.429000
Maximum2023-04-05 22:45:40.842000
2023-04-25T09:50:52.361972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:52.471339image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

object_datetostarton_kst
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct277
Distinct (%)78.0%
Missing316
Missing (%)47.1%
Memory size5.4 KiB
2023-04-06 06:50:35.415000
 
3
2023-04-06 07:05:31.939000
 
3
2023-04-06 07:24:28.645000
 
2
2023-04-06 07:34:28.413000
 
2
2023-04-06 07:34:18.988000
 
2
Other values (272)
343 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters9230
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)56.6%

Sample

1st row2023-04-06 07:24:28.645000
2nd row2023-04-06 07:24:28.645000
3rd row2023-04-06 07:23:28.152000
4th row2023-04-06 07:24:02.671000
5th row2023-04-06 07:24:02.671000

Common Values

ValueCountFrequency (%)
2023-04-06 06:50:35.415000 3
 
0.4%
2023-04-06 07:05:31.939000 3
 
0.4%
2023-04-06 07:24:28.645000 2
 
0.3%
2023-04-06 07:34:28.413000 2
 
0.3%
2023-04-06 07:34:18.988000 2
 
0.3%
2023-04-06 07:30:03.931000 2
 
0.3%
2023-04-06 07:37:53.823000 2
 
0.3%
2023-04-06 07:32:05.324000 2
 
0.3%
2023-04-06 07:31:21.897000 2
 
0.3%
2023-04-06 07:29:32.890000 2
 
0.3%
Other values (267) 333
49.6%
(Missing) 316
47.1%

Length

2023-04-25T09:50:52.602852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-04-06 329
46.3%
2023-04-05 15
 
2.1%
2023-03-18 4
 
0.6%
06:50:35.415000 3
 
0.4%
2023-03-17 3
 
0.4%
07:05:31.939000 3
 
0.4%
19:10:23.610000 2
 
0.3%
07:24:20.539000 2
 
0.3%
07:20:09.709000 2
 
0.3%
07:34:08.973000 2
 
0.3%
Other values (274) 345
48.6%

Most occurring characters

ValueCountFrequency (%)
0 2697
29.2%
2 1063
 
11.5%
3 806
 
8.7%
- 710
 
7.7%
: 710
 
7.7%
4 578
 
6.3%
7 502
 
5.4%
6 499
 
5.4%
355
 
3.8%
. 355
 
3.8%
Other values (4) 955
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7100
76.9%
Other Punctuation 1065
 
11.5%
Dash Punctuation 710
 
7.7%
Space Separator 355
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2697
38.0%
2 1063
 
15.0%
3 806
 
11.4%
4 578
 
8.1%
7 502
 
7.1%
6 499
 
7.0%
1 299
 
4.2%
5 274
 
3.9%
9 208
 
2.9%
8 174
 
2.5%
Other Punctuation
ValueCountFrequency (%)
: 710
66.7%
. 355
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 710
100.0%
Space Separator
ValueCountFrequency (%)
355
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2697
29.2%
2 1063
 
11.5%
3 806
 
8.7%
- 710
 
7.7%
: 710
 
7.7%
4 578
 
6.3%
7 502
 
5.4%
6 499
 
5.4%
355
 
3.8%
. 355
 
3.8%
Other values (4) 955
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2697
29.2%
2 1063
 
11.5%
3 806
 
8.7%
- 710
 
7.7%
: 710
 
7.7%
4 578
 
6.3%
7 502
 
5.4%
6 499
 
5.4%
355
 
3.8%
. 355
 
3.8%
Other values (4) 955
 
10.3%
Distinct201
Distinct (%)98.5%
Missing467
Missing (%)69.6%
Memory size5.4 KiB
Minimum2023-03-17 11:18:43.853000
Maximum2023-04-05 22:45:51.172000
2023-04-25T09:50:52.727852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:52.837224image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

object_datetosubmit_kst
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct201
Distinct (%)98.5%
Missing467
Missing (%)69.6%
Memory size5.4 KiB
2023-04-06 07:05:30.715000
 
2
2023-04-06 07:29:49.759000
 
2
2023-04-06 07:15:00.498000
 
2
2023-04-06 07:41:13.215000
 
1
2023-04-05 20:42:15.830000
 
1
Other values (196)
196 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters5304
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)97.1%

Sample

1st row2023-04-06 07:31:01.174000
2nd row2023-04-06 07:31:05.786000
3rd row2023-04-06 07:31:10.385000
4th row2023-04-06 07:31:18.290000
5th row2023-04-06 07:31:23.794000

Common Values

ValueCountFrequency (%)
2023-04-06 07:05:30.715000 2
 
0.3%
2023-04-06 07:29:49.759000 2
 
0.3%
2023-04-06 07:15:00.498000 2
 
0.3%
2023-04-06 07:41:13.215000 1
 
0.1%
2023-04-05 20:42:15.830000 1
 
0.1%
2023-04-06 07:40:40.813000 1
 
0.1%
2023-04-06 07:40:40.420000 1
 
0.1%
2023-04-06 07:40:43.981000 1
 
0.1%
2023-04-06 07:40:54.615000 1
 
0.1%
2023-04-06 07:40:57.585000 1
 
0.1%
Other values (191) 191
28.5%
(Missing) 467
69.6%

Length

2023-04-25T09:50:52.962225image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-04-06 191
46.8%
2023-04-05 7
 
1.7%
07:29:49.759000 2
 
0.5%
07:15:00.498000 2
 
0.5%
2023-03-18 2
 
0.5%
07:05:30.715000 2
 
0.5%
2023-03-17 2
 
0.5%
2023-03-22 2
 
0.5%
07:31:23.794000 1
 
0.2%
07:31:35.468000 1
 
0.2%
Other values (196) 196
48.0%

Most occurring characters

ValueCountFrequency (%)
0 1542
29.1%
2 553
 
10.4%
3 467
 
8.8%
- 408
 
7.7%
: 408
 
7.7%
4 406
 
7.7%
7 306
 
5.8%
6 277
 
5.2%
204
 
3.8%
. 204
 
3.8%
Other values (4) 529
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4080
76.9%
Other Punctuation 612
 
11.5%
Dash Punctuation 408
 
7.7%
Space Separator 204
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1542
37.8%
2 553
 
13.6%
3 467
 
11.4%
4 406
 
10.0%
7 306
 
7.5%
6 277
 
6.8%
1 162
 
4.0%
5 159
 
3.9%
8 109
 
2.7%
9 99
 
2.4%
Other Punctuation
ValueCountFrequency (%)
: 408
66.7%
. 204
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 408
100.0%
Space Separator
ValueCountFrequency (%)
204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1542
29.1%
2 553
 
10.4%
3 467
 
8.8%
- 408
 
7.7%
: 408
 
7.7%
4 406
 
7.7%
7 306
 
5.8%
6 277
 
5.2%
204
 
3.8%
. 204
 
3.8%
Other values (4) 529
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1542
29.1%
2 553
 
10.4%
3 467
 
8.8%
- 408
 
7.7%
: 408
 
7.7%
4 406
 
7.7%
7 306
 
5.8%
6 277
 
5.2%
204
 
3.8%
. 204
 
3.8%
Other values (4) 529
 
10.0%

object_maxattempts
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing671
Missing (%)100.0%
Memory size5.4 KiB

object_maxsubmits
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing671
Missing (%)100.0%
Memory size5.4 KiB

object_maxscore
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing671
Missing (%)100.0%
Memory size2.7 KiB

edapp_id
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer
344 
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer2
318 
http://app.milkt.co.kr/kr.hbstudy.apphbstudy
 
9

Length

Max length58
Median length57
Mean length57.299553
Min length44

Characters and Unicode

Total characters38448
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer
2nd rowhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer
3rd rowhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer
4th rowhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer
5th rowhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer

Common Values

ValueCountFrequency (%)
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer 344
51.3%
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer2 318
47.4%
http://app.milkt.co.kr/kr.hbstudy.apphbstudy 9
 
1.3%

Length

2023-04-25T09:50:53.071597image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:53.180972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer 344
51.3%
http://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayer2 318
47.4%
http://app.milkt.co.kr/kr.hbstudy.apphbstudy 9
 
1.3%

Most occurring characters

ValueCountFrequency (%)
. 4679
 
12.2%
p 2693
 
7.0%
t 2693
 
7.0%
r 2666
 
6.9%
a 2666
 
6.9%
c 2657
 
6.9%
k 2013
 
5.2%
h 2013
 
5.2%
/ 2013
 
5.2%
l 1995
 
5.2%
Other values (13) 12360
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30767
80.0%
Other Punctuation 7363
 
19.2%
Decimal Number 318
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 2693
 
8.8%
t 2693
 
8.8%
r 2666
 
8.7%
a 2666
 
8.7%
c 2657
 
8.6%
k 2013
 
6.5%
h 2013
 
6.5%
l 1995
 
6.5%
o 1995
 
6.5%
d 1342
 
4.4%
Other values (9) 8034
26.1%
Other Punctuation
ValueCountFrequency (%)
. 4679
63.5%
/ 2013
27.3%
: 671
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30767
80.0%
Common 7681
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2693
 
8.8%
t 2693
 
8.8%
r 2666
 
8.7%
a 2666
 
8.7%
c 2657
 
8.6%
k 2013
 
6.5%
h 2013
 
6.5%
l 1995
 
6.5%
o 1995
 
6.5%
d 1342
 
4.4%
Other values (9) 8034
26.1%
Common
ValueCountFrequency (%)
. 4679
60.9%
/ 2013
26.2%
: 671
 
8.7%
2 318
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4679
 
12.2%
p 2693
 
7.0%
t 2693
 
7.0%
r 2666
 
6.9%
a 2666
 
6.9%
c 2657
 
6.9%
k 2013
 
5.2%
h 2013
 
5.2%
/ 2013
 
5.2%
l 1995
 
5.2%
Other values (13) 12360
32.1%

edapp_type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
SoftwareApplication
671 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters12749
Distinct characters14
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSoftwareApplication
2nd rowSoftwareApplication
3rd rowSoftwareApplication
4th rowSoftwareApplication
5th rowSoftwareApplication

Common Values

ValueCountFrequency (%)
SoftwareApplication 671
100.0%

Length

2023-04-25T09:50:53.274728image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:53.386838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
softwareapplication 671
100.0%

Most occurring characters

ValueCountFrequency (%)
o 1342
10.5%
t 1342
10.5%
a 1342
10.5%
p 1342
10.5%
i 1342
10.5%
S 671
 
5.3%
f 671
 
5.3%
w 671
 
5.3%
r 671
 
5.3%
e 671
 
5.3%
Other values (4) 2684
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11407
89.5%
Uppercase Letter 1342
 
10.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1342
11.8%
t 1342
11.8%
a 1342
11.8%
p 1342
11.8%
i 1342
11.8%
f 671
5.9%
w 671
5.9%
r 671
5.9%
e 671
5.9%
l 671
5.9%
Other values (2) 1342
11.8%
Uppercase Letter
ValueCountFrequency (%)
S 671
50.0%
A 671
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12749
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1342
10.5%
t 1342
10.5%
a 1342
10.5%
p 1342
10.5%
i 1342
10.5%
S 671
 
5.3%
f 671
 
5.3%
w 671
 
5.3%
r 671
 
5.3%
e 671
 
5.3%
Other values (4) 2684
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12749
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1342
10.5%
t 1342
10.5%
a 1342
10.5%
p 1342
10.5%
i 1342
10.5%
S 671
 
5.3%
f 671
 
5.3%
w 671
 
5.3%
r 671
 
5.3%
e 671
 
5.3%
Other values (4) 2684
21.1%

edapp_name
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
kr.co.chunjae.android.cjhtmlplayer
344 
kr.co.chunjae.android.cjhtmlplayer2
318 
kr.hbstudy.apphbstudy
 
9

Length

Max length35
Median length34
Mean length34.299553
Min length21

Characters and Unicode

Total characters23015
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowkr.co.chunjae.android.cjhtmlplayer
2nd rowkr.co.chunjae.android.cjhtmlplayer
3rd rowkr.co.chunjae.android.cjhtmlplayer
4th rowkr.co.chunjae.android.cjhtmlplayer
5th rowkr.co.chunjae.android.cjhtmlplayer

Common Values

ValueCountFrequency (%)
kr.co.chunjae.android.cjhtmlplayer 344
51.3%
kr.co.chunjae.android.cjhtmlplayer2 318
47.4%
kr.hbstudy.apphbstudy 9
 
1.3%

Length

2023-04-25T09:50:53.465838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:53.566839image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
kr.co.chunjae.android.cjhtmlplayer 344
51.3%
kr.co.chunjae.android.cjhtmlplayer2 318
47.4%
kr.hbstudy.apphbstudy 9
 
1.3%

Most occurring characters

ValueCountFrequency (%)
. 2666
11.6%
a 1995
 
8.7%
r 1995
 
8.7%
c 1986
 
8.6%
h 1342
 
5.8%
d 1342
 
5.8%
e 1324
 
5.8%
l 1324
 
5.8%
o 1324
 
5.8%
n 1324
 
5.8%
Other values (11) 6393
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20031
87.0%
Other Punctuation 2666
 
11.6%
Decimal Number 318
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1995
10.0%
r 1995
10.0%
c 1986
9.9%
h 1342
 
6.7%
d 1342
 
6.7%
e 1324
 
6.6%
l 1324
 
6.6%
o 1324
 
6.6%
n 1324
 
6.6%
j 1324
 
6.6%
Other values (9) 4751
23.7%
Other Punctuation
ValueCountFrequency (%)
. 2666
100.0%
Decimal Number
ValueCountFrequency (%)
2 318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20031
87.0%
Common 2984
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1995
10.0%
r 1995
10.0%
c 1986
9.9%
h 1342
 
6.7%
d 1342
 
6.7%
e 1324
 
6.6%
l 1324
 
6.6%
o 1324
 
6.6%
n 1324
 
6.6%
j 1324
 
6.6%
Other values (9) 4751
23.7%
Common
ValueCountFrequency (%)
. 2666
89.3%
2 318
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2666
11.6%
a 1995
 
8.7%
r 1995
 
8.7%
c 1986
 
8.6%
h 1342
 
5.8%
d 1342
 
5.8%
e 1324
 
5.8%
l 1324
 
5.8%
o 1324
 
5.8%
n 1324
 
5.8%
Other values (11) 6393
27.8%

edapp_description
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
노드 Html 학습창
662 
밀크T초등_문제은행
 
5
밀크T초등_영상플레이어
 
2
밀크T초등_통합학습창
 
2

Length

Max length12
Median length11
Mean length10.995529
Min length10

Characters and Unicode

Total characters7378
Distinct characters28
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노드 Html 학습창
2nd row노드 Html 학습창
3rd row노드 Html 학습창
4th row노드 Html 학습창
5th row노드 Html 학습창

Common Values

ValueCountFrequency (%)
노드 Html 학습창 662
98.7%
밀크T초등_문제은행 5
 
0.7%
밀크T초등_영상플레이어 2
 
0.3%
밀크T초등_통합학습창 2
 
0.3%

Length

2023-04-25T09:50:53.633486image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:53.848659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
노드 662
33.2%
html 662
33.2%
학습창 662
33.2%
밀크t초등_문제은행 5
 
0.3%
밀크t초등_영상플레이어 2
 
0.1%
밀크t초등_통합학습창 2
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1324
17.9%
664
9.0%
664
9.0%
664
9.0%
662
9.0%
H 662
9.0%
t 662
9.0%
m 662
9.0%
l 662
9.0%
662
9.0%
Other values (18) 90
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3388
45.9%
Lowercase Letter 1986
26.9%
Space Separator 1324
 
17.9%
Uppercase Letter 671
 
9.1%
Connector Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
664
19.6%
664
19.6%
664
19.6%
662
19.5%
662
19.5%
9
 
0.3%
9
 
0.3%
9
 
0.3%
9
 
0.3%
5
 
0.1%
Other values (11) 31
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
t 662
33.3%
m 662
33.3%
l 662
33.3%
Uppercase Letter
ValueCountFrequency (%)
H 662
98.7%
T 9
 
1.3%
Space Separator
ValueCountFrequency (%)
1324
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3388
45.9%
Latin 2657
36.0%
Common 1333
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
664
19.6%
664
19.6%
664
19.6%
662
19.5%
662
19.5%
9
 
0.3%
9
 
0.3%
9
 
0.3%
9
 
0.3%
5
 
0.1%
Other values (11) 31
 
0.9%
Latin
ValueCountFrequency (%)
H 662
24.9%
t 662
24.9%
m 662
24.9%
l 662
24.9%
T 9
 
0.3%
Common
ValueCountFrequency (%)
1324
99.3%
_ 9
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3990
54.1%
Hangul 3388
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1324
33.2%
H 662
16.6%
t 662
16.6%
m 662
16.6%
l 662
16.6%
_ 9
 
0.2%
T 9
 
0.2%
Hangul
ValueCountFrequency (%)
664
19.6%
664
19.6%
664
19.6%
662
19.5%
662
19.5%
9
 
0.3%
9
 
0.3%
9
 
0.3%
9
 
0.3%
5
 
0.1%
Other values (11) 31
 
0.9%

edapp_version
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
1.1.16
654 
1.1.13
 
8
1.9.80
 
7
1.9.79
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters4026
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.1.16
2nd row1.1.16
3rd row1.1.16
4th row1.1.16
5th row1.1.16

Common Values

ValueCountFrequency (%)
1.1.16 654
97.5%
1.1.13 8
 
1.2%
1.9.80 7
 
1.0%
1.9.79 2
 
0.3%

Length

2023-04-25T09:50:53.958657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:54.036725image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1.1.16 654
97.5%
1.1.13 8
 
1.2%
1.9.80 7
 
1.0%
1.9.79 2
 
0.3%

Most occurring characters

ValueCountFrequency (%)
1 1995
49.6%
. 1342
33.3%
6 654
 
16.2%
9 11
 
0.3%
3 8
 
0.2%
8 7
 
0.2%
0 7
 
0.2%
7 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2684
66.7%
Other Punctuation 1342
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1995
74.3%
6 654
 
24.4%
9 11
 
0.4%
3 8
 
0.3%
8 7
 
0.3%
0 7
 
0.3%
7 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 1342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1995
49.6%
. 1342
33.3%
6 654
 
16.2%
9 11
 
0.3%
3 8
 
0.2%
8 7
 
0.2%
0 7
 
0.2%
7 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1995
49.6%
. 1342
33.3%
6 654
 
16.2%
9 11
 
0.3%
3 8
 
0.2%
8 7
 
0.2%
0 7
 
0.2%
7 2
 
< 0.1%

referrer_id
Categorical

Distinct234
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://app.milkt.co.kr/T0VE01U06003
86 
http://app.milkt.co.kr/T0ME01U12010
 
40
http://app.milkt.co.kr/T0ME01U05010
 
33
http://app.milkt.co.kr/T0ME01U04010
 
17
http://app.milkt.co.kr/T0BE00U24006
 
17
Other values (229)
478 

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters23485
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)16.5%

Sample

1st rowhttp://app.milkt.co.kr/T0VE01U04009
2nd rowhttp://app.milkt.co.kr/T0VE01U04009
3rd rowhttp://app.milkt.co.kr/T0VE01U06003
4th rowhttp://app.milkt.co.kr/T0VE01U06003
5th rowhttp://app.milkt.co.kr/T0EE01U04008

Common Values

ValueCountFrequency (%)
http://app.milkt.co.kr/T0VE01U06003 86
 
12.8%
http://app.milkt.co.kr/T0ME01U12010 40
 
6.0%
http://app.milkt.co.kr/T0ME01U05010 33
 
4.9%
http://app.milkt.co.kr/T0ME01U04010 17
 
2.5%
http://app.milkt.co.kr/T0BE00U24006 17
 
2.5%
http://app.milkt.co.kr/T0VE01U05006 15
 
2.2%
http://app.milkt.co.kr/T0BE00U19006 15
 
2.2%
http://app.milkt.co.kr/T0EE01U05009 13
 
1.9%
http://app.milkt.co.kr/T0VE01U02004 13
 
1.9%
http://app.milkt.co.kr/T0VE01U01004 10
 
1.5%
Other values (224) 412
61.4%

Length

2023-04-25T09:50:54.083597image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://app.milkt.co.kr/t0ve01u06003 86
 
12.8%
http://app.milkt.co.kr/t0me01u12010 40
 
6.0%
http://app.milkt.co.kr/t0me01u05010 33
 
4.9%
http://app.milkt.co.kr/t0me01u04010 17
 
2.5%
http://app.milkt.co.kr/t0be00u24006 17
 
2.5%
http://app.milkt.co.kr/t0ve01u05006 15
 
2.2%
http://app.milkt.co.kr/t0be00u19006 15
 
2.2%
http://app.milkt.co.kr/t0ve01u02004 13
 
1.9%
http://app.milkt.co.kr/t0ee01u05009 13
 
1.9%
http://app.milkt.co.kr/t0ve01u01004 10
 
1.5%
Other values (224) 412
61.4%

Most occurring characters

ValueCountFrequency (%)
0 2911
 
12.4%
p 2013
 
8.6%
t 2013
 
8.6%
/ 2013
 
8.6%
. 2013
 
8.6%
k 1342
 
5.7%
1 973
 
4.1%
E 761
 
3.2%
U 672
 
2.9%
T 672
 
2.9%
Other values (35) 8102
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10736
45.7%
Decimal Number 5294
22.5%
Other Punctuation 4697
20.0%
Uppercase Letter 2758
 
11.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 761
27.6%
U 672
24.4%
T 672
24.4%
V 196
 
7.1%
M 158
 
5.7%
B 94
 
3.4%
K 54
 
2.0%
W 29
 
1.1%
A 24
 
0.9%
S 21
 
0.8%
Other values (11) 77
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
p 2013
18.8%
t 2013
18.8%
k 1342
12.5%
h 671
 
6.2%
r 671
 
6.2%
o 671
 
6.2%
c 671
 
6.2%
l 671
 
6.2%
i 671
 
6.2%
m 671
 
6.2%
Decimal Number
ValueCountFrequency (%)
0 2911
55.0%
1 973
 
18.4%
2 278
 
5.3%
3 261
 
4.9%
6 224
 
4.2%
4 180
 
3.4%
5 177
 
3.3%
9 134
 
2.5%
8 88
 
1.7%
7 68
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 2013
42.9%
. 2013
42.9%
: 671
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 13494
57.5%
Common 9991
42.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2013
14.9%
t 2013
14.9%
k 1342
9.9%
E 761
 
5.6%
U 672
 
5.0%
T 672
 
5.0%
h 671
 
5.0%
r 671
 
5.0%
o 671
 
5.0%
c 671
 
5.0%
Other values (22) 3337
24.7%
Common
ValueCountFrequency (%)
0 2911
29.1%
/ 2013
20.1%
. 2013
20.1%
1 973
 
9.7%
: 671
 
6.7%
2 278
 
2.8%
3 261
 
2.6%
6 224
 
2.2%
4 180
 
1.8%
5 177
 
1.8%
Other values (3) 290
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2911
 
12.4%
p 2013
 
8.6%
t 2013
 
8.6%
/ 2013
 
8.6%
. 2013
 
8.6%
k 1342
 
5.7%
1 973
 
4.1%
E 761
 
3.2%
U 672
 
2.9%
T 672
 
2.9%
Other values (35) 8102
34.5%

referrer_type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
DigitalResource
671 

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters10065
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDigitalResource
2nd rowDigitalResource
3rd rowDigitalResource
4th rowDigitalResource
5th rowDigitalResource

Common Values

ValueCountFrequency (%)
DigitalResource 671
100.0%

Length

2023-04-25T09:50:54.177342image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:54.239849image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
digitalresource 671
100.0%

Most occurring characters

ValueCountFrequency (%)
i 1342
13.3%
e 1342
13.3%
D 671
 
6.7%
g 671
 
6.7%
t 671
 
6.7%
a 671
 
6.7%
l 671
 
6.7%
R 671
 
6.7%
s 671
 
6.7%
o 671
 
6.7%
Other values (3) 2013
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8723
86.7%
Uppercase Letter 1342
 
13.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1342
15.4%
e 1342
15.4%
g 671
7.7%
t 671
7.7%
a 671
7.7%
l 671
7.7%
s 671
7.7%
o 671
7.7%
u 671
7.7%
r 671
7.7%
Uppercase Letter
ValueCountFrequency (%)
D 671
50.0%
R 671
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10065
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1342
13.3%
e 1342
13.3%
D 671
 
6.7%
g 671
 
6.7%
t 671
 
6.7%
a 671
 
6.7%
l 671
 
6.7%
R 671
 
6.7%
s 671
 
6.7%
o 671
 
6.7%
Other values (3) 2013
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10065
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1342
13.3%
e 1342
13.3%
D 671
 
6.7%
g 671
 
6.7%
t 671
 
6.7%
a 671
 
6.7%
l 671
 
6.7%
R 671
 
6.7%
s 671
 
6.7%
o 671
 
6.7%
Other values (3) 2013
20.0%
Distinct41
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
T_EBOOK_B
127 
T_MDONG_H
90 
T_KIDS_CC
60 
T_KIDS_CD
57 
T_KIDS_CB
41 
Other values (36)
296 

Length

Max length18
Median length9
Mean length9.3278689
Min length6

Characters and Unicode

Total characters6259
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.0%

Sample

1st rowT_MDONG_A
2nd rowT_MDONG_A
3rd rowT_MDONG_H
4th rowT_MDONG_H
5th rowT_KIDS_CB

Common Values

ValueCountFrequency (%)
T_EBOOK_B 127
18.9%
T_MDONG_H 90
13.4%
T_KIDS_CC 60
 
8.9%
T_KIDS_CD 57
 
8.5%
T_KIDS_CB 41
 
6.1%
T_KIDS_HHJ 33
 
4.9%
T_MDONG_P 31
 
4.6%
T_KIDS_CA 22
 
3.3%
T_MDONG_A 20
 
3.0%
T_KIDS_ML 18
 
2.7%
Other values (31) 172
25.6%

Length

2023-04-25T09:50:54.286730image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t_ebook_b 127
18.6%
t_mdong_h 90
13.2%
t_kids_cc 60
 
8.8%
t_kids_cd 57
 
8.4%
t_kids_cb 41
 
6.0%
t_kids_hhj 33
 
4.8%
t_mdong_p 31
 
4.6%
t_kids_ca 22
 
3.2%
t_mdong_a 20
 
2.9%
t_kids_ml 18
 
2.6%
Other values (32) 182
26.7%

Most occurring characters

ValueCountFrequency (%)
_ 1288
20.6%
T 719
11.5%
D 577
9.2%
O 532
8.5%
K 415
 
6.6%
I 321
 
5.1%
B 309
 
4.9%
S 297
 
4.7%
C 292
 
4.7%
M 245
 
3.9%
Other values (35) 1264
20.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4800
76.7%
Connector Punctuation 1288
 
20.6%
Lowercase Letter 161
 
2.6%
Space Separator 10
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 719
15.0%
D 577
12.0%
O 532
11.1%
K 415
8.6%
I 321
 
6.7%
B 309
 
6.4%
S 297
 
6.2%
C 292
 
6.1%
M 245
 
5.1%
N 221
 
4.6%
Other values (15) 872
18.2%
Lowercase Letter
ValueCountFrequency (%)
n 22
13.7%
i 19
11.8%
o 15
9.3%
a 12
 
7.5%
s 11
 
6.8%
g 11
 
6.8%
c 9
 
5.6%
r 9
 
5.6%
h 8
 
5.0%
k 8
 
5.0%
Other values (8) 37
23.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1288
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4961
79.3%
Common 1298
 
20.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 719
14.5%
D 577
11.6%
O 532
10.7%
K 415
8.4%
I 321
 
6.5%
B 309
 
6.2%
S 297
 
6.0%
C 292
 
5.9%
M 245
 
4.9%
N 221
 
4.5%
Other values (33) 1033
20.8%
Common
ValueCountFrequency (%)
_ 1288
99.2%
10
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 1288
20.6%
T 719
11.5%
D 577
9.2%
O 532
8.5%
K 415
 
6.6%
I 321
 
5.1%
B 309
 
4.9%
S 297
 
4.7%
C 292
 
4.7%
M 245
 
3.9%
Other values (35) 1264
20.2%
Distinct14
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
V
196 
M
158 
B
88 
E
83 
K
54 
Other values (9)
92 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters671
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st rowV
2nd rowV
3rd rowV
4th rowV
5th rowE

Common Values

ValueCountFrequency (%)
V 196
29.2%
M 158
23.5%
B 88
13.1%
E 83
12.4%
K 54
 
8.0%
W 24
 
3.6%
S 21
 
3.1%
O 17
 
2.5%
X 14
 
2.1%
N 11
 
1.6%
Other values (4) 5
 
0.7%

Length

2023-04-25T09:50:54.398562image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
v 196
29.2%
m 158
23.5%
b 88
13.1%
e 83
12.4%
k 54
 
8.0%
w 24
 
3.6%
s 21
 
3.1%
o 17
 
2.5%
x 14
 
2.1%
n 11
 
1.6%
Other values (4) 5
 
0.7%

Most occurring characters

ValueCountFrequency (%)
V 196
29.2%
M 158
23.5%
B 88
13.1%
E 83
12.4%
K 54
 
8.0%
W 24
 
3.6%
S 21
 
3.1%
O 17
 
2.5%
X 14
 
2.1%
N 11
 
1.6%
Other values (4) 5
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 671
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V 196
29.2%
M 158
23.5%
B 88
13.1%
E 83
12.4%
K 54
 
8.0%
W 24
 
3.6%
S 21
 
3.1%
O 17
 
2.5%
X 14
 
2.1%
N 11
 
1.6%
Other values (4) 5
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 671
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
V 196
29.2%
M 158
23.5%
B 88
13.1%
E 83
12.4%
K 54
 
8.0%
W 24
 
3.6%
S 21
 
3.1%
O 17
 
2.5%
X 14
 
2.1%
N 11
 
1.6%
Other values (4) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
V 196
29.2%
M 158
23.5%
B 88
13.1%
E 83
12.4%
K 54
 
8.0%
W 24
 
3.6%
S 21
 
3.1%
O 17
 
2.5%
X 14
 
2.1%
N 11
 
1.6%
Other values (4) 5
 
0.7%

referrer_extensions_assignmentgrade
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1341282
Minimum0
Maximum9
Zeros473
Zeros (%)70.5%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-04-25T09:50:54.580643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2520069
Coefficient of variation (CV)1.9856723
Kurtosis4.3982721
Mean1.1341282
Median Absolute Deviation (MAD)0
Skewness2.2420137
Sum761
Variance5.071535
MonotonicityNot monotonic
2023-04-25T09:50:54.680606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 473
70.5%
2 41
 
6.1%
1 38
 
5.7%
3 32
 
4.8%
9 29
 
4.3%
5 26
 
3.9%
4 19
 
2.8%
6 13
 
1.9%
ValueCountFrequency (%)
0 473
70.5%
1 38
 
5.7%
2 41
 
6.1%
3 32
 
4.8%
4 19
 
2.8%
5 26
 
3.9%
6 13
 
1.9%
9 29
 
4.3%
ValueCountFrequency (%)
9 29
 
4.3%
6 13
 
1.9%
5 26
 
3.9%
4 19
 
2.8%
3 32
 
4.8%
2 41
 
6.1%
1 38
 
5.7%
0 473
70.5%

referrer_extensions_assignmentsemester
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)0.5%
Missing90
Missing (%)13.4%
Memory size5.4 KiB
1.0
543 
0.0
 
31
2.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1743
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 543
80.9%
0.0 31
 
4.6%
2.0 7
 
1.0%
(Missing) 90
 
13.4%

Length

2023-04-25T09:50:54.780604image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:54.868603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1.0 543
93.5%
0.0 31
 
5.3%
2.0 7
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 612
35.1%
. 581
33.3%
1 543
31.2%
2 7
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1162
66.7%
Other Punctuation 581
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 612
52.7%
1 543
46.7%
2 7
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 581
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1743
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 612
35.1%
. 581
33.3%
1 543
31.2%
2 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 612
35.1%
. 581
33.3%
1 543
31.2%
2 7
 
0.4%
Distinct18
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8464978
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-04-25T09:50:54.966602image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q36
95-th percentile15
Maximum62
Range61
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.9009882
Coefficient of variation (CV)1.0112433
Kurtosis30.562565
Mean4.8464978
Median Absolute Deviation (MAD)2
Skewness3.9753131
Sum3252
Variance24.019685
MonotonicityNot monotonic
2023-04-25T09:50:55.078605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3 123
18.3%
2 113
16.8%
1 100
14.9%
4 99
14.8%
6 98
14.6%
5 46
 
6.9%
15 24
 
3.6%
8 19
 
2.8%
20 18
 
2.7%
12 12
 
1.8%
Other values (8) 19
 
2.8%
ValueCountFrequency (%)
1 100
14.9%
2 113
16.8%
3 123
18.3%
4 99
14.8%
5 46
 
6.9%
6 98
14.6%
7 3
 
0.4%
8 19
 
2.8%
11 3
 
0.4%
12 12
 
1.8%
ValueCountFrequency (%)
62 1
 
0.1%
34 1
 
0.1%
20 18
2.7%
18 3
 
0.4%
17 1
 
0.1%
16 5
 
0.7%
15 24
3.6%
13 2
 
0.3%
12 12
1.8%
11 3
 
0.4%

referrer_extensions_assignmentmchapter
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
0
629 
1
 
24
2
 
16
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters671
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%

Length

2023-04-25T09:50:55.179606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:55.303603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 671
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 629
93.7%
1 24
 
3.6%
2 16
 
2.4%
5 2
 
0.3%
Distinct38
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2023-03-12 15:00:00
Maximum2023-07-03 15:00:00
2023-04-25T09:50:55.414607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:55.580644image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

referrer_extensions_assignmentprogday_kst
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct38
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-04-06 00:00:00
433 
2023-04-05 00:00:00
78 
2023-04-07 00:00:00
 
27
2023-04-03 00:00:00
 
25
2023-04-04 00:00:00
 
23
Other values (33)
85 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters12749
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)1.6%

Sample

1st row2023-04-06 00:00:00
2nd row2023-04-06 00:00:00
3rd row2023-04-06 00:00:00
4th row2023-04-06 00:00:00
5th row2023-04-07 00:00:00

Common Values

ValueCountFrequency (%)
2023-04-06 00:00:00 433
64.5%
2023-04-05 00:00:00 78
 
11.6%
2023-04-07 00:00:00 27
 
4.0%
2023-04-03 00:00:00 25
 
3.7%
2023-04-04 00:00:00 23
 
3.4%
2023-04-10 00:00:00 7
 
1.0%
2023-03-13 00:00:00 7
 
1.0%
2023-04-14 00:00:00 5
 
0.7%
2023-03-31 00:00:00 5
 
0.7%
2023-03-30 00:00:00 5
 
0.7%
Other values (28) 56
 
8.3%

Length

2023-04-25T09:50:55.667612image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00:00 670
49.9%
2023-04-06 433
32.3%
2023-04-05 78
 
5.8%
2023-04-07 27
 
2.0%
2023-04-03 25
 
1.9%
2023-04-04 24
 
1.8%
2023-04-10 7
 
0.5%
2023-03-13 7
 
0.5%
2023-03-30 5
 
0.4%
2023-04-26 5
 
0.4%
Other values (29) 61
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 5983
46.9%
2 1365
 
10.7%
- 1342
 
10.5%
: 1342
 
10.5%
3 749
 
5.9%
671
 
5.3%
4 656
 
5.1%
6 445
 
3.5%
5 95
 
0.7%
1 52
 
0.4%
Other values (3) 49
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9394
73.7%
Dash Punctuation 1342
 
10.5%
Other Punctuation 1342
 
10.5%
Space Separator 671
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5983
63.7%
2 1365
 
14.5%
3 749
 
8.0%
4 656
 
7.0%
6 445
 
4.7%
5 95
 
1.0%
1 52
 
0.6%
7 37
 
0.4%
9 8
 
0.1%
8 4
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1342
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1342
100.0%
Space Separator
ValueCountFrequency (%)
671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12749
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5983
46.9%
2 1365
 
10.7%
- 1342
 
10.5%
: 1342
 
10.5%
3 749
 
5.9%
671
 
5.3%
4 656
 
5.1%
6 445
 
3.5%
5 95
 
0.7%
1 52
 
0.4%
Other values (3) 49
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12749
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5983
46.9%
2 1365
 
10.7%
- 1342
 
10.5%
: 1342
 
10.5%
3 749
 
5.9%
671
 
5.3%
4 656
 
5.1%
6 445
 
3.5%
5 95
 
0.7%
1 52
 
0.4%
Other values (3) 49
 
0.4%

session_id
Categorical

Distinct285
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
http://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197f
 
9
http://app.milkt.co.kr/sessions/0fa29964-6e4c-45cb-9dd0-650b5b0401b3
 
9
http://app.milkt.co.kr/sessions/3e5be9f9-1916-4af2-a427-113538c254ba
 
8
http://app.milkt.co.kr/sessions/21db0e4f-2849-44f7-be11-4643fdb93e57
 
8
http://app.milkt.co.kr/sessions/556efafb-c1d9-4292-b421-6b50f137fbea
 
8
Other values (280)
629 

Length

Max length68
Median length68
Mean length68
Min length68

Characters and Unicode

Total characters45628
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)16.1%

Sample

1st rowhttp://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197f
2nd rowhttp://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197f
3rd rowhttp://app.milkt.co.kr/sessions/9632a5fd-5ecd-4c5e-9763-3713d523a7bd
4th rowhttp://app.milkt.co.kr/sessions/674e7a89-2284-4fbc-84c5-015428df53cc
5th rowhttp://app.milkt.co.kr/sessions/c57e5550-4077-4fc8-83c7-b9939abf43f8

Common Values

ValueCountFrequency (%)
http://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197f 9
 
1.3%
http://app.milkt.co.kr/sessions/0fa29964-6e4c-45cb-9dd0-650b5b0401b3 9
 
1.3%
http://app.milkt.co.kr/sessions/3e5be9f9-1916-4af2-a427-113538c254ba 8
 
1.2%
http://app.milkt.co.kr/sessions/21db0e4f-2849-44f7-be11-4643fdb93e57 8
 
1.2%
http://app.milkt.co.kr/sessions/556efafb-c1d9-4292-b421-6b50f137fbea 8
 
1.2%
http://app.milkt.co.kr/sessions/4010fca5-21fd-43ae-a084-b1e977801ce3 7
 
1.0%
http://app.milkt.co.kr/sessions/a383af5f-d524-41ad-901f-f58aa2156d40 7
 
1.0%
http://app.milkt.co.kr/sessions/bacfd798-5bb6-4e94-9687-38935a090d40 7
 
1.0%
http://app.milkt.co.kr/sessions/e24fee1a-aeaa-44ce-8b75-b94e69fc9761 6
 
0.9%
http://app.milkt.co.kr/sessions/8278893b-4958-49c2-bc6d-556813a60077 6
 
0.9%
Other values (275) 596
88.8%

Length

2023-04-25T09:50:55.761354image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
http://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197f 9
 
1.3%
http://app.milkt.co.kr/sessions/0fa29964-6e4c-45cb-9dd0-650b5b0401b3 9
 
1.3%
http://app.milkt.co.kr/sessions/3e5be9f9-1916-4af2-a427-113538c254ba 8
 
1.2%
http://app.milkt.co.kr/sessions/21db0e4f-2849-44f7-be11-4643fdb93e57 8
 
1.2%
http://app.milkt.co.kr/sessions/556efafb-c1d9-4292-b421-6b50f137fbea 8
 
1.2%
http://app.milkt.co.kr/sessions/4010fca5-21fd-43ae-a084-b1e977801ce3 7
 
1.0%
http://app.milkt.co.kr/sessions/a383af5f-d524-41ad-901f-f58aa2156d40 7
 
1.0%
http://app.milkt.co.kr/sessions/bacfd798-5bb6-4e94-9687-38935a090d40 7
 
1.0%
http://app.milkt.co.kr/sessions/9b18c8cd-59fe-4b90-a270-164a58ce0e0f 6
 
0.9%
http://app.milkt.co.kr/sessions/33c6e7f1-2397-4aa4-82a5-91dc8ffc1c8c 6
 
0.9%
Other values (275) 596
88.8%

Most occurring characters

ValueCountFrequency (%)
s 2684
 
5.9%
- 2684
 
5.9%
/ 2684
 
5.9%
a 2113
 
4.6%
p 2013
 
4.4%
. 2013
 
4.4%
t 2013
 
4.4%
e 1959
 
4.3%
c 1937
 
4.2%
4 1863
 
4.1%
Other values (21) 23665
51.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23913
52.4%
Decimal Number 13663
29.9%
Other Punctuation 5368
 
11.8%
Dash Punctuation 2684
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2684
11.2%
a 2113
 
8.8%
p 2013
 
8.4%
t 2013
 
8.4%
e 1959
 
8.2%
c 1937
 
8.1%
b 1456
 
6.1%
k 1342
 
5.6%
o 1342
 
5.6%
i 1342
 
5.6%
Other values (7) 5712
23.9%
Decimal Number
ValueCountFrequency (%)
4 1863
13.6%
9 1519
11.1%
8 1416
10.4%
2 1338
9.8%
6 1312
9.6%
3 1279
9.4%
1 1278
9.4%
7 1237
9.1%
5 1232
9.0%
0 1189
8.7%
Other Punctuation
ValueCountFrequency (%)
/ 2684
50.0%
. 2013
37.5%
: 671
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 2684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23913
52.4%
Common 21715
47.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2684
11.2%
a 2113
 
8.8%
p 2013
 
8.4%
t 2013
 
8.4%
e 1959
 
8.2%
c 1937
 
8.1%
b 1456
 
6.1%
k 1342
 
5.6%
o 1342
 
5.6%
i 1342
 
5.6%
Other values (7) 5712
23.9%
Common
ValueCountFrequency (%)
- 2684
12.4%
/ 2684
12.4%
. 2013
9.3%
4 1863
8.6%
9 1519
 
7.0%
8 1416
 
6.5%
2 1338
 
6.2%
6 1312
 
6.0%
3 1279
 
5.9%
1 1278
 
5.9%
Other values (4) 4329
19.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2684
 
5.9%
- 2684
 
5.9%
/ 2684
 
5.9%
a 2113
 
4.6%
p 2013
 
4.4%
. 2013
 
4.4%
t 2013
 
4.4%
e 1959
 
4.3%
c 1937
 
4.2%
4 1863
 
4.1%
Other values (21) 23665
51.9%

session_type
Categorical

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Session
671 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4697
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSession
2nd rowSession
3rd rowSession
4th rowSession
5th rowSession

Common Values

ValueCountFrequency (%)
Session 671
100.0%

Length

2023-04-25T09:50:55.855100image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:55.904995image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
session 671
100.0%

Most occurring characters

ValueCountFrequency (%)
s 1342
28.6%
S 671
14.3%
e 671
14.3%
i 671
14.3%
o 671
14.3%
n 671
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4026
85.7%
Uppercase Letter 671
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1342
33.3%
e 671
16.7%
i 671
16.7%
o 671
16.7%
n 671
16.7%
Uppercase Letter
ValueCountFrequency (%)
S 671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4697
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1342
28.6%
S 671
14.3%
e 671
14.3%
i 671
14.3%
o 671
14.3%
n 671
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 1342
28.6%
S 671
14.3%
e 671
14.3%
i 671
14.3%
o 671
14.3%
n 671
14.3%
Distinct286
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2023-01-02 04:40:50.218000
Maximum2023-04-05 22:22:15.567000
2023-04-25T09:50:55.983125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:56.093872image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct286
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-01-05 16:08:09.328000
 
9
2023-01-09 12:25:15.449000
 
9
2023-02-01 20:58:51.620000
 
8
2023-02-07 17:33:47.142000
 
8
2023-03-03 07:07:37.166000
 
8
Other values (281)
629 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters17446
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)16.2%

Sample

1st row2023-01-05 16:08:09.328000
2nd row2023-01-05 16:08:09.328000
3rd row2023-01-10 09:17:52.173000
4th row2023-01-12 20:57:53.708000
5th row2023-01-02 19:54:34.128000

Common Values

ValueCountFrequency (%)
2023-01-05 16:08:09.328000 9
 
1.3%
2023-01-09 12:25:15.449000 9
 
1.3%
2023-02-01 20:58:51.620000 8
 
1.2%
2023-02-07 17:33:47.142000 8
 
1.2%
2023-03-03 07:07:37.166000 8
 
1.2%
2023-01-23 13:38:53.187000 7
 
1.0%
2023-03-17 19:21:15.111000 7
 
1.0%
2023-03-22 16:48:12.429000 7
 
1.0%
2023-01-27 19:18:03.703000 6
 
0.9%
2023-03-02 20:19:35.549000 6
 
0.9%
Other values (276) 596
88.8%

Length

2023-04-25T09:50:56.187628image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-01-09 42
 
3.1%
2023-01-02 33
 
2.5%
2023-03-02 24
 
1.8%
2023-04-04 20
 
1.5%
2023-01-10 19
 
1.4%
2023-03-22 19
 
1.4%
2023-04-03 18
 
1.3%
2023-01-27 18
 
1.3%
2023-02-01 17
 
1.3%
2023-03-17 16
 
1.2%
Other values (358) 1116
83.2%

Most occurring characters

ValueCountFrequency (%)
0 4556
26.1%
2 2533
14.5%
3 1617
 
9.3%
1 1519
 
8.7%
- 1342
 
7.7%
: 1342
 
7.7%
671
 
3.8%
. 671
 
3.8%
5 645
 
3.7%
4 623
 
3.6%
Other values (4) 1927
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13420
76.9%
Other Punctuation 2013
 
11.5%
Dash Punctuation 1342
 
7.7%
Space Separator 671
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4556
33.9%
2 2533
18.9%
3 1617
 
12.0%
1 1519
 
11.3%
5 645
 
4.8%
4 623
 
4.6%
7 560
 
4.2%
8 488
 
3.6%
9 472
 
3.5%
6 407
 
3.0%
Other Punctuation
ValueCountFrequency (%)
: 1342
66.7%
. 671
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1342
100.0%
Space Separator
ValueCountFrequency (%)
671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4556
26.1%
2 2533
14.5%
3 1617
 
9.3%
1 1519
 
8.7%
- 1342
 
7.7%
: 1342
 
7.7%
671
 
3.8%
. 671
 
3.8%
5 645
 
3.7%
4 623
 
3.6%
Other values (4) 1927
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4556
26.1%
2 2533
14.5%
3 1617
 
9.3%
1 1519
 
8.7%
- 1342
 
7.7%
: 1342
 
7.7%
671
 
3.8%
. 671
 
3.8%
5 645
 
3.7%
4 623
 
3.6%
Other values (4) 1927
11.0%
Distinct285
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
leeso0215
 
9
mingi0828
 
9
psh1026
 
8
seonho0609
 
8
sunu0528
 
8
Other values (280)
629 

Length

Max length13
Median length11
Mean length8.3457526
Min length5

Characters and Unicode

Total characters5600
Distinct characters60
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)16.1%

Sample

1st rowleeso0215
2nd rowleeso0215
3rd rowlisjm1
4th rowtnwjd8209
5th rowsws0324

Common Values

ValueCountFrequency (%)
leeso0215 9
 
1.3%
mingi0828 9
 
1.3%
psh1026 8
 
1.2%
seonho0609 8
 
1.2%
sunu0528 8
 
1.2%
Ian0415 7
 
1.0%
P20171202 7
 
1.0%
Jaeha0331 7
 
1.0%
cosua1010 6
 
0.9%
Seoa170331 6
 
0.9%
Other values (275) 596
88.8%

Length

2023-04-25T09:50:56.281403image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
leeso0215 9
 
1.3%
mingi0828 9
 
1.3%
psh1026 8
 
1.2%
seonho0609 8
 
1.2%
sunu0528 8
 
1.2%
ian0415 7
 
1.0%
p20171202 7
 
1.0%
jaeha0331 7
 
1.0%
sojeong1108 6
 
0.9%
yunshu 6
 
0.9%
Other values (275) 596
88.8%

Most occurring characters

ValueCountFrequency (%)
0 528
 
9.4%
1 516
 
9.2%
2 327
 
5.8%
o 270
 
4.8%
n 255
 
4.6%
a 240
 
4.3%
7 230
 
4.1%
s 220
 
3.9%
e 211
 
3.8%
i 195
 
3.5%
Other values (50) 2608
46.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2863
51.1%
Decimal Number 2496
44.6%
Uppercase Letter 241
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 270
 
9.4%
n 255
 
8.9%
a 240
 
8.4%
s 220
 
7.7%
e 211
 
7.4%
i 195
 
6.8%
h 160
 
5.6%
u 145
 
5.1%
j 141
 
4.9%
y 132
 
4.6%
Other values (16) 894
31.2%
Uppercase Letter
ValueCountFrequency (%)
J 32
13.3%
Y 19
 
7.9%
S 18
 
7.5%
L 17
 
7.1%
D 16
 
6.6%
H 13
 
5.4%
O 13
 
5.4%
N 12
 
5.0%
M 12
 
5.0%
P 11
 
4.6%
Other values (14) 78
32.4%
Decimal Number
ValueCountFrequency (%)
0 528
21.2%
1 516
20.7%
2 327
13.1%
7 230
9.2%
8 188
 
7.5%
3 167
 
6.7%
6 146
 
5.8%
9 144
 
5.8%
4 127
 
5.1%
5 123
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 3104
55.4%
Common 2496
44.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 270
 
8.7%
n 255
 
8.2%
a 240
 
7.7%
s 220
 
7.1%
e 211
 
6.8%
i 195
 
6.3%
h 160
 
5.2%
u 145
 
4.7%
j 141
 
4.5%
y 132
 
4.3%
Other values (40) 1135
36.6%
Common
ValueCountFrequency (%)
0 528
21.2%
1 516
20.7%
2 327
13.1%
7 230
9.2%
8 188
 
7.5%
3 167
 
6.7%
6 146
 
5.8%
9 144
 
5.8%
4 127
 
5.1%
5 123
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 528
 
9.4%
1 516
 
9.2%
2 327
 
5.8%
o 270
 
4.8%
n 255
 
4.6%
a 240
 
4.3%
7 230
 
4.1%
s 220
 
3.9%
e 211
 
3.8%
i 195
 
3.5%
Other values (50) 2608
46.6%
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
1.0
671 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2013
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 671
100.0%

Length

2023-04-25T09:50:56.375126image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:56.459469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1.0 671
100.0%

Most occurring characters

ValueCountFrequency (%)
1 671
33.3%
. 671
33.3%
0 671
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1342
66.7%
Other Punctuation 671
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 671
50.0%
0 671
50.0%
Other Punctuation
ValueCountFrequency (%)
. 671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2013
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 671
33.3%
. 671
33.3%
0 671
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2013
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 671
33.3%
. 671
33.3%
0 671
33.3%
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
1.0.2
671 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters3355
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0.2
2nd row1.0.2
3rd row1.0.2
4th row1.0.2
5th row1.0.2

Common Values

ValueCountFrequency (%)
1.0.2 671
100.0%

Length

2023-04-25T09:50:56.525640image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:56.608230image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1.0.2 671
100.0%

Most occurring characters

ValueCountFrequency (%)
. 1342
40.0%
1 671
20.0%
0 671
20.0%
2 671
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2013
60.0%
Other Punctuation 1342
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 671
33.3%
0 671
33.3%
2 671
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1342
40.0%
1 671
20.0%
0 671
20.0%
2 671
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1342
40.0%
1 671
20.0%
0 671
20.0%
2 671
20.0%

extensions_timezone
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Asia/Seoul
670 
America/Denver
 
1

Length

Max length14
Median length10
Mean length10.005961
Min length10

Characters and Unicode

Total characters6714
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowAsia/Seoul
2nd rowAsia/Seoul
3rd rowAsia/Seoul
4th rowAsia/Seoul
5th rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Seoul 670
99.9%
America/Denver 1
 
0.1%

Length

2023-04-25T09:50:56.670979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-25T09:50:56.764728image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/seoul 670
99.9%
america/denver 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 673
10.0%
A 671
10.0%
i 671
10.0%
a 671
10.0%
/ 671
10.0%
s 670
10.0%
S 670
10.0%
o 670
10.0%
u 670
10.0%
l 670
10.0%
Other values (6) 7
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4701
70.0%
Uppercase Letter 1342
 
20.0%
Other Punctuation 671
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 673
14.3%
i 671
14.3%
a 671
14.3%
s 670
14.3%
o 670
14.3%
u 670
14.3%
l 670
14.3%
r 2
 
< 0.1%
m 1
 
< 0.1%
c 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
A 671
50.0%
S 670
49.9%
D 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6043
90.0%
Common 671
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 673
11.1%
A 671
11.1%
i 671
11.1%
a 671
11.1%
s 670
11.1%
S 670
11.1%
o 670
11.1%
u 670
11.1%
l 670
11.1%
r 2
 
< 0.1%
Other values (5) 5
 
0.1%
Common
ValueCountFrequency (%)
/ 671
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 673
10.0%
A 671
10.0%
i 671
10.0%
a 671
10.0%
/ 671
10.0%
s 670
10.0%
S 670
10.0%
o 670
10.0%
u 670
10.0%
l 670
10.0%
Other values (6) 7
 
0.1%
Distinct670
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2023-04-05 22:30:56.449000
Maximum2023-04-05 22:45:56.397000
2023-04-25T09:50:56.842849image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:56.973727image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

in_datetime_kst
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct671
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-04-06 07:30:56.449597
 
1
2023-04-06 07:41:01.174578
 
1
2023-04-06 07:41:06.002461
 
1
2023-04-06 07:41:09.559715
 
1
2023-04-06 07:41:09.565351
 
1
Other values (666)
666 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters17446
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique671 ?
Unique (%)100.0%

Sample

1st row2023-04-06 07:30:56.449597
2nd row2023-04-06 07:30:56.455742
3rd row2023-04-06 07:31:00.631917
4th row2023-04-06 07:31:05.075568
5th row2023-04-06 07:31:06.428467

Common Values

ValueCountFrequency (%)
2023-04-06 07:30:56.449597 1
 
0.1%
2023-04-06 07:41:01.174578 1
 
0.1%
2023-04-06 07:41:06.002461 1
 
0.1%
2023-04-06 07:41:09.559715 1
 
0.1%
2023-04-06 07:41:09.565351 1
 
0.1%
2023-04-06 07:41:10.106507 1
 
0.1%
2023-04-06 07:41:12.134729 1
 
0.1%
2023-04-06 07:41:12.210084 1
 
0.1%
2023-04-06 07:41:13.297877 1
 
0.1%
2023-04-06 07:41:14.534575 1
 
0.1%
Other values (661) 661
98.5%

Length

2023-04-25T09:50:57.089906image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-04-06 671
50.0%
07:31:12.483361 1
 
0.1%
07:31:28.852083 1
 
0.1%
07:31:00.631917 1
 
0.1%
07:31:05.075568 1
 
0.1%
07:31:06.428467 1
 
0.1%
07:31:06.441689 1
 
0.1%
07:31:10.196614 1
 
0.1%
07:31:10.958983 1
 
0.1%
07:31:11.971801 1
 
0.1%
Other values (662) 662
49.3%

Most occurring characters

ValueCountFrequency (%)
0 3299
18.9%
2 2010
11.5%
3 1699
9.7%
4 1566
9.0%
- 1342
7.7%
: 1342
7.7%
6 1242
 
7.1%
7 1209
 
6.9%
1 680
 
3.9%
671
 
3.8%
Other values (4) 2386
13.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13420
76.9%
Other Punctuation 2013
 
11.5%
Dash Punctuation 1342
 
7.7%
Space Separator 671
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3299
24.6%
2 2010
15.0%
3 1699
12.7%
4 1566
11.7%
6 1242
 
9.3%
7 1209
 
9.0%
1 680
 
5.1%
5 660
 
4.9%
9 539
 
4.0%
8 516
 
3.8%
Other Punctuation
ValueCountFrequency (%)
: 1342
66.7%
. 671
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1342
100.0%
Space Separator
ValueCountFrequency (%)
671
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3299
18.9%
2 2010
11.5%
3 1699
9.7%
4 1566
9.0%
- 1342
7.7%
: 1342
7.7%
6 1242
 
7.1%
7 1209
 
6.9%
1 680
 
3.9%
671
 
3.8%
Other values (4) 2386
13.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3299
18.9%
2 2010
11.5%
3 1699
9.7%
4 1566
9.0%
- 1342
7.7%
: 1342
7.7%
6 1242
 
7.1%
7 1209
 
6.9%
1 680
 
3.9%
671
 
3.8%
Other values (4) 2386
13.7%

Interactions

2023-04-25T09:50:46.686651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:40.612737image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:45.180564image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:47.809056image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:42.763628image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:46.453439image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:47.936979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:43.778787image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-25T09:50:46.571015image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2023-04-25T09:50:57.203089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
actor_extensions_userpostreferrer_extensions_assignmentgradereferrer_extensions_assignmentlchapteractor_extensions_usertypeactor_extensions_usertypenameactor_extensions_usertypedescriptionactor_extensions_userlevelactor_extensions_usergradeactionedapp_idedapp_nameedapp_descriptionedapp_versionreferrer_extensions_assignmenttypereferrer_extensions_assignmentsubjectidreferrer_extensions_assignmentsemesterreferrer_extensions_assignmentmchapterreferrer_extensions_assignmentprogday_kstextensions_timezone
actor_extensions_userpost1.000-0.1230.0630.7450.7450.7450.7540.7520.2320.5200.5200.5630.6070.5090.5290.6030.6430.5960.769
referrer_extensions_assignmentgrade-0.1231.000-0.3520.1240.1240.1240.9080.8910.0280.2630.2630.2040.2370.5240.5610.4310.3910.4200.163
referrer_extensions_assignmentlchapter0.063-0.3521.0000.0320.0320.0320.1720.1380.0570.1800.1800.0000.1060.8640.3700.2910.1150.2070.000
actor_extensions_usertype0.7450.1240.0321.0000.9900.9900.1620.1460.0000.0960.0960.0000.0000.2840.1200.0510.0350.0000.000
actor_extensions_usertypename0.7450.1240.0320.9901.0000.9900.1620.1460.0000.0960.0960.0000.0000.2840.1200.0510.0350.0000.000
actor_extensions_usertypedescription0.7450.1240.0320.9900.9901.0000.1620.1460.0000.0960.0960.0000.0000.2840.1200.0510.0350.0000.000
actor_extensions_userlevel0.7540.9080.1720.1620.1620.1621.0000.9960.0960.2330.2330.1520.2090.9140.7650.1390.4040.5000.000
actor_extensions_usergrade0.7520.8910.1380.1460.1460.1460.9961.0000.0490.2440.2440.1900.2630.4220.4620.1390.3990.4150.159
action0.2320.0280.0570.0000.0000.0000.0960.0491.0000.0000.0000.0000.0160.0000.0670.0000.0000.0000.000
edapp_id0.5200.2630.1800.0960.0960.0960.2330.2440.0001.0001.0000.7050.7100.8100.6350.3000.3610.5110.000
edapp_name0.5200.2630.1800.0960.0960.0960.2330.2440.0001.0001.0000.7050.7100.8100.6350.3000.3610.5110.000
edapp_description0.5630.2040.0000.0000.0000.0000.1520.1900.0000.7050.7051.0000.6380.9040.3560.3720.3590.7210.000
edapp_version0.6070.2370.1060.0000.0000.0000.2090.2630.0160.7100.7100.6381.0000.7320.5840.2990.5800.6690.000
referrer_extensions_assignmenttype0.5090.5240.8640.2840.2840.2840.9140.4220.0000.8100.8100.9040.7321.0000.6920.9160.6430.3190.000
referrer_extensions_assignmentsubjectid0.5290.5610.3700.1200.1200.1200.7650.4620.0670.6350.6350.3560.5840.6921.0000.4690.8190.3230.000
referrer_extensions_assignmentsemester0.6030.4310.2910.0510.0510.0510.1390.1390.0000.3000.3000.3720.2990.9160.4691.0000.1930.3290.000
referrer_extensions_assignmentmchapter0.6430.3910.1150.0350.0350.0350.4040.3990.0000.3610.3610.3590.5800.6430.8190.1931.0000.3750.000
referrer_extensions_assignmentprogday_kst0.5960.4200.2070.0000.0000.0000.5000.4150.0000.5110.5110.7210.6690.3190.3230.3290.3751.0000.973
extensions_timezone0.7690.1630.0000.0000.0000.0000.0000.1590.0000.0000.0000.0000.0000.0000.0000.0000.0000.9731.000

Missing values

2023-04-25T09:50:48.320895image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-04-25T09:50:48.783677image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-04-25T09:50:49.186646image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

contextidtypeactor_idactor_typeactor_extensions_useridactor_extensions_usertypeactor_extensions_usertypenameactor_extensions_usertypedescriptionactor_extensions_userlevelactor_extensions_usergradeactor_extensions_userpostactor_extensions_userteacheridactor_extensions_userparentidactioneventtimeeventtime_kstobject_idobject_typeobject_nameobject_mediatypeobject_learningobjectivesobject_datetostartonobject_datetostarton_kstobject_datetosubmitobject_datetosubmit_kstobject_maxattemptsobject_maxsubmitsobject_maxscoreedapp_idedapp_typeedapp_nameedapp_descriptionedapp_versionreferrer_idreferrer_typereferrer_extensions_assignmenttypereferrer_extensions_assignmentsubjectidreferrer_extensions_assignmentgradereferrer_extensions_assignmentsemesterreferrer_extensions_assignmentlchapterreferrer_extensions_assignmentmchapterreferrer_extensions_assignmentprogdayreferrer_extensions_assignmentprogday_kstsession_idsession_typesession_startedattimesession_startedattime_kstsession_extensions_useridextensions_caliperversionextensions_caliperappversionextensions_timezonein_timestampin_datetime_kst
0http://purl.imsglobal.org/ctx/caliper/v1p1urn:uuid:690e96a0-a203-435b-b157-5737cf5a5c65AssignableEventhttp://app.milkt.co.kr/person/0bedc637-bd61-4a31-924d-79dbd379969ePersonleeso021511학습생(정)정상적인 결제를 거친 학습생15017mteacher7004coolk2mSubmitted2023-04-05 22:31:01.1742023-04-06 07:31:01.174000http://app.milkt.co.kr/T0VE01U04009AssignableDigitalResource누구의 발자국일까?NoneNone2023-04-05 22:24:28.6452023-04-06 07:24:28.6450002023-04-05 22:31:01.1742023-04-06 07:31:01.174000NaNNaNNaNhttp://app.milkt.co.kr/kr.co.chunjae.android.cjhtmlplayerSoftwareApplicationkr.co.chunjae.android.cjhtmlplayer노드 Html 학습창1.1.16http://app.milkt.co.kr/T0VE01U04009DigitalResourceT_MDONG_AV01.0402023-04-05 15:00:002023-04-06 00:00:00http://app.milkt.co.kr/sessions/62a822c2-a1d9-486e-a675-3b19af9a197fSession2023-01-05 07:08:09.3282023-01-05 16:08:09.328000leeso02151.01.0.2Asia/Seoul2023-04-05 22:30:56.4492023-04-06 07:30:56.449597
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